About This Course
What you will learn:


Study Introduction to Statistics Online Course and Improve Your Data Analysis
Our Online Statistics course is perfect for anybody needing to gain a better understanding of statistics. Regardless of whether statistics is a new field for you or you just need to refresh your statistical knowledge, this statistics online course will further your knowledge of statistics and enhance your ability to make informed decisions using the data available to you.
This introductory online statistics course combines gives you the knowledge, and skills to analyze data with confidence. Throughout the course, you will be given opportunities to investigate the use and application of data structures to reallife problems and circumstances.
The statistics course online will give you a deep learning and complete introduction to the world of statistics, starting with the allimportant concepts of data science and data collection practices. With those concepts bedded down, you will go on to learn how to summarize statistical information using graphs, charts, and numbers. You will discover how to determine probabilities and form an understanding of how probabilities are used in the decisionmaking process.
You’ll learn:
Statistical analysis
Statistical concepts
Statistical methods
Statistical models
Statistical processing
Statistical reasoning
Statistical thinking
You’ll also discover the difference between statistics and machine learning. It’s important to note that statistics is one of the most important parts of both data analytics and machine learning. It helps a data analyst see patterns in data that they couldn't see before, and allows them to then analyze these.
Courses for Success’ statistics and data classes online will show you how to visualize and measure data relationships. You will also learn how to effectively utilize data for forecasting and prediction purposes. The statistics training online will also explore the fundamentals of statistical inference and introduce you to the concept of statistically significant results.
This statistics class online training consistently makes use of real data and an array of practical examples sourced across the statistical spectrum. You will use exploratory data related to business and industry, sports, politics, health care and medicine, education, politics, the social sciences, and news events.
There is no need to be concerned about having to perform intricate calculations as the online statistics class will introduce you to a range of free online programs that will assist you in making calculations.
After taking statistics online course you will have no trouble in being able to apply and interpret fundamental statistical procedures effectively.
What you will learn with our Introduction to Statistics Online Course
Quantitative Data
Displaying Quantitative Data & Quantitative Reasoning
Displaying Qualitative Data
Linear Regression
Probability Models
The Key to Inference
Testing Hypotheses About Proportions
Introduction to Statistics Online Course  Requirements
The Introduction to Statistics Course is delivered 100 percent online 24/7.
To successfully complete this course, a student must:
Have access to the internet and the necessary technical skills to navigate the online learning resources
Have access to any mobile device with internet connectivity (laptop, desktop, tablet)
Be a selfdirected learner
Possess sound language and literacy skills
Quick Course Facts
Course content is structured for easy comprehension
Registered students gain unrestricted access to the Introduction to Statistics Course
All course material is available online 24/7 and can be accessed using any device
Study online from anywhere in your own time at your own pace
All students who complete the course will be awarded with a certificate of completion
For any additional questions please see our comprehensive FAQS tab above.
Introduction to Statistics Online Course Outline
Chapter 1: Introduction
This data analysis statistics course introduces you to the concept of data science and analytics, which can take you into the world of business analytics, cloud computing, app development, computer programming, environmental engineering, mobile development and so much more.
Topics to be discussed include:
Why Learn Statistics?
Chapter 2: The Basics of Statistics
It's a field of study that deals with data analysis. What is data, by the way? Information is data! It's information with context and meaning, not just a tangle of numbers, in particular. Plan, tools, and methods for collecting, displaying, analyzing, and interpreting data are all part of modern statistics.
Topics to be discussed include:
Various Variables
It Starts with a question
Chapter 3: Data Collection Using Sampling
Taking a census of the entire population, as you taught in Chapter 2, is frequently prohibitively costly and timeconsuming. As a result, you'll need to take a random sample of the population. We'll look at numerous strategies to ensure that the sample appropriately reflects the larger population in this chapter. You'll see how highquality data isn't created by accident... though it does play a part.
Topics to be discussed include:
Sampling Methods
Systematic random sampling
Stratified random sampling
Cluster sampling
Chapter 4: Designing Experiments to Collect Data
Experiments have provided us with a lot of information on health, nutrition, and human behavior. Without deliberate trials, breakthroughs in agriculture that help feed us all and advances in medicine that aid you when you're sick would not have been feasible. We'd have to rely on guessing, luck, folklore, or doing things the way we've always done them if we didn't have them.
Topics to be discussed include:
Designed Experiments: The Basics
Control
Randomization
Blinding
Replication
Observational Studies
Chapter 5: Summary
Every statistical study begins with a question. It's critical to select samples that accurately reflect the population as a whole in order to obtain credible results. The key is to use random sampling. And every experiment that is designed to answer a question must be controlled, randomized, blinded, and reproducible.
Lesson 2: Quantitative Data: From Averages to zScores
Chapter 1: Introduction
One of my keys aims for this course is for you to be able to understand statistics and statistical results that you see in your daily life, interpret them correctly, and even build your own sound statistical studies. Statistics knowledge will aid you in interpreting data and making sound judgments.
Chapter 2: Journey to the Center of Your Data
Look over your data before you start any computations or graphs, especially if you didn't collect and compile it yourself. It's what one of my graduate school professors referred to as "eyeballing" your data. When you eyeball the data, you skim it to get a sense of the size of the values, look for missing or incorrect numbers, and try to notice any values that don't make sense.
Topics to be discussed include:
Calculating the Mean
Finding the Median
Comparing Means and Medians
Chapter 3: Variability: The Spice of Statistics Life
Consider how people differ in a variety of ways. To name a few characteristics, we differ in age, weight, height, gender, race, family history, income, and education. Throughout our lifetimes, we all encounter changes in our income and weight, as well as changes in typical health metrics like temperature, heart rate, and blood pressure.
Topics to be discussed include:
Determining the range
Standard Deviation
Chapter 4: All About zScores
Here's an example of a common method that incorporates some of the concepts covered in this lecture. It also introduces a concept that will be revisited later in the course.
Topics to be discussed include:
What are Zscores
Another Option
Chapter 5: Summary
You will learn some basic descriptive statistics in this course that you'll need practically every time you study quantitative data. The mean or median can be used to describe the center or average of quantitative data. The mean takes into account all of the data, but extreme results, or outliers, may have an impact. To get the middle number, the median uses the order of the data.
Lesson 3: Displaying Quantitative Data: Dots, Plots, and Histograms
Chapter 1: Introduction
Nobody wants to spend time staring at numbers in columns and rows, trying to see patterns. Data visualizations make it easier to find trends and detect unexpected values, as well as being more pleasing to the eye. If you have to show data at work, you'll almost certainly do it with a graph. The plots and graphs you'll see in this session are the statistician's basic graphical tools.
Chapter 2: Displaying Data: Dots, Stems, and Leaves
It's simpler to see the distribution, or pattern of variation, in statistical data when it's displayed on a graph. Dot plots are frequently used by statisticians as a first step in visualizing data distribution.
Topics to be discussed include:
Dot plots
SteamandLeaf plots
SteamandLeaf plots: White Refusal Rate
Chapter 3: Histograms
The charts you saw in Chapter 2 may get cluttered with larger data sets. The histogram, which is usually a preferable solution for huge data sets, is covered in this chapter. You split your data into equalwidth "bins" to make a histogram. The number of data values that fall within each bin is then counted.
Topics to be discussed include:
What should I look for in a Histogram
Where would you guess the mean and median for this variable would fall in the histogram
Where would you guess the mean and median are in this histogram?
What stands out to you?
Chapter 4: Advanced Visuals: FiveNumber Summaries and Box Plots
When performing these kinds of comparisons, a box plot is a useful tool. This is how one appears. This one compares the results of five tests aimed at determining the speed of light.
Topics to be discussed include:
FiveNumber Summaries
Minimum
First quartile
Median
Third quartile
Maximum
BoxPlots
Chapter 5: Summary
You will learn about a statistician's core graphical tools for visualizing quantitative data in this session. As computers become more powerful, the discipline of statistical graphics continues to evolve. The basic graphs from the class may usually be modified using most software products. The Minitab software suite, for example, has seven options for making dot plots and four options for creating histograms.
Lesson 4: Displaying Qualitative Data: Percentages, Charts, and Graphs
Chapter 1: Introduction
In Lesson 4, we'll concentrate on qualitative data—how to summarize, show, and truly comprehend it. Percentages, pie charts, and bar charts will all be discussed. They're the kinds of summaries you'll see in the news and on the internet. We'll look at correlations between two qualitative variables after we've covered the basics.
Chapter 2: Percentages and Pies
First and foremost, qualitative data is concerned with attributes, features, or categories, such as male or female, agree or disagree, and Republican, Democratic, or Independent. Categorical data is another name for it. The first step is to generate a frequency table that lists the various categories as well as the number of observatories in each category.
Topics to be discussed include:
Percentages Versus Counts
Pie Charts
Chapter 3: Bar Charts and TwoWay Tables
The use of bar charts is just as frequent as the use of pie charts. I'm sure you've seen them before, and you've probably even made them. They may display a greater number of categories and are more adaptable than a pie chart. Even if your data is incomplete and the percentages do not add up to 100 percent, you can still make them. Each category in a bar chart is represented by a vertical or horizontal bar.
Topics to be discussed include:
Twoway tables
Chapter 4: Beyond the Basics: Is There an Association?
We can now search for possible links or linkages between category variables. We'll use the twoway tables and conditional distributions that we discussed in Chapter 3 to do this. However, before we return to the tables, let's create some stacked bar charts to accompany them.
Topics to be discussed include:
Stacked Bar Charts
Association int Twoway Tables
Chapter 5: Summary
In Lesson 4, you’ll learn about qualitative data. Frequency tables, pie charts, bar charts, Pareto charts, stacked bar charts, and twoway tables were among the data visualization options you considered. Conditional distributions provided you actual insight into data, such as the differences between male and female survey respondents or organic and conventionally cultivated commodities.
Lesson 5: Is There a Link? Scatterplots and Correlation
Chapter 1: Introduction
We'll use a different set of procedures with quantitative data than we used in Lesson 4 when we looked at the relationship between categorical variables. You'll learn how to create and understand scatterplots in order to visualize the relationship between variables. To examine for patterns and trends across time, you'll use time plots and line plots.
Chapter 2: Scatterplots
A scatterplot is a graph with one variable on the horizontal (or x) axis and the other variable on the vertical (or y) axis. (Think "Y travels to the sky" if you're having difficulties remembering which is which.)
Topics to be discussed include:
Direction of Association
Form of Association
Strength of Association
Unusual Points
Chapter 3: Times and Lines
Topics to be discussed include:
Time Plots
Why Look for Trends or Cycles Over Time?
Chapter 4: Correlation: How Strong Is the Link?
Correlation refers to a specific number that you calculate using two quantitative variables. The number you get from the calculation tells you about the strength and direction of the association you've seen in a scatterplot.
Topics to be discussed include:
Using the Pearson Correlation Coefficient
A Correlation Formula
Beware of Outliers!
Correlation Doesn’t Man Causation
Chapter 5: Summary
In Lesson 5, you will see how to display and measure the association between two quantitative variables. Making a scatterplot should always be your first step when exploring relationships between variables. A scatterplot helps you see the direction, form, and strength of any association, plus you can spot unusual values and outliers.
A time plot is a scatterplot where the horizontal variable is some measure of time, like days, months, or years. They're useful for seeing trends over time in all kinds of data, from sports to business to weather forecasting to public health. A line plot is similar to a time plot except the points are connected with lines. Connecting the points can make patterns more visible and allow you to distinguish one series of data values from another.
Lesson 6: Linear Regression: How Can We Predict the Future?
Chapter 1: Introduction
In this lesson, you'll learn to make predictions that are based on data. You'll use methods that statisticians rely on daily, and examine data from sports, business, government, and environmental science.
In this lesson, we'll go beyond describing and measuring the association between two quantitative variables. You'll learn to use a process called linear regression to find an equation that models the pattern in a scatterplot.
Chapter 2: Don't Forget Your Lines!
Before we jump into finding lines to model data, we'll review the equations of lines. Then we'll discuss how statisticians use linear equations. The thought processes we'll use in this lesson are a little different from the thought processes of basic algebra. In case you need a reminder, slope is a number that measures the slant or steepness of the line. It can be positive, negative, zero, or even undefined. The situations we study in statistics will have either a positive slope (to go along with positive associations and correlations) or a negative slope (to go along with negative associations and correlations). In statistics, slope tells us how the data variables change in relation to one another.
Topics to be discussed include:
Other Ways to Write the Equation
Roles of the Variables
Lines as Models in Statistics
Chapter 3: What's My Line?
We first need to define what we mean by "best fit." Look at the graph below showing a line that models the pattern of the eight data points.
Topics to be discussed include:
WorldRecord Times Revisited
Predictiong Wind Speed in Hurricanes
Chapter 4: How Good Is My Regression Model?
We'll look at ways to visualize and explain data collected over time in this chapter. You'll learn how to use time plots and line plots to look at topics like quarterly sales, yearly advances in hurricane predictions, and sporting event trends.
Topics to be discussed include:
. What is R 2?
Crime and Poverty Revisited
Weight in Motion Again
Prediction CO 2 levels
Chapter 5: Summary
You will find the equation of a linear model for two quantitative variables using linear regression in Lesson 6. One variable is designated as the predictor, while the other is designated as the response. Then you use the least squares approach to fit a line to the data. The slope and intercept of the line of best fit were calculated using this method.
Lesson 7: What's the Chance of That? Probability Concepts
Chapter 1: Introduction to Probability Theory
The topic of probability and statistics will be the subject of this and the following lessons. To progress beyond the descriptive statistics we covered in the first six sessions, you'll need a basic understanding of statistics probability distributions. In the final lessons of the course, we'll use probability to build the framework we'll need to go on to inferential statistics.
Topics to be discussed include:
What is Probability?
Chapter 2: Probability Basic Training
Probability allows us to characterize and quantify the likelihood of uncertain events. There is no uncertainty and no need for probability if an event always occurs or never occurs. However, due to randomness and unpredictability, many events are unpredictable, from a simple coin toss at the start of a baseball game to the performance of a complex stock transaction.
Topics to be discussed include:
Calculating Probabilities
Probability Facts
Chapter 3: Probability Rules!
Two or more simple events combine to form compound events. When you toss a coin once, you get a simple event with two outcomes: heads or tails. If you toss the coin three times, you'll get a compound event composed of three basic events. We'll look at a rule for calculating compound event probability in this chapter.
Topics to be discussed include:
Independence and the Product Rule
Chapter 4: The Sum Rule and Conditional Probability
Let's keep talking about compound event probability. First, I'll demonstrate how to calculate probabilities for events including the word or, such as the likelihood of rolling a seven or an eleven on dice. After that, we'll take a quick look at conditional probabilities.
Topics to be discussed include:
Sum Rule
Conditional Probability
Chapter 5: Summary
This part of the statistics and data professional certificate covers the fundamentals of probability in this session. You will see how to use theoretical and empirical models to determine probability. You’ll use probability in scenarios as simple as card and dice games to more sophisticated ones like determining the likelihood of at least one inaccurate drug test result.
Lesson 8: Probability Models: What's Normal?
Chapter 1: Introduction
Many of the general rules that influence probability were covered in Lesson 7. In this session, we'll apply some of these concepts, but our main focus will be on probability models, particularly the normal model. You've seen a normal model if you've ever heard the term "bell curve" or seen a picture of one.
Chapter 2: Probability Models: What Should You Expect?
A probability model (or distribution) for a random process specifies the process's various outcomes as well as the likelihood of each result. The probability model for rolling two dice and then adding the numbers that come up is shown in the table below.
Topics to be discussed include:
Expected Value
Chapter 3: The Normal Model
A normal model will not fully match a data set at every point. It does, however, provide us with a summary that helps us to acquire insight, evaluate probabilities, and make predictions. What we can learn without a model is restricted to the sample data available. We can make larger population generalizations using a model.
Topics to be discussed include:
Properties of Normal Model
The 689599.7% Rule
Chapter 4: Estimating Normal Probabilities
We're ready to move on to more detailed normal probability calculations now that you've seen the normal model. Every computation can be simplified by following one rule. Over intervals, we'll always calculate normal probability. A range of numbers is referred to as an interval. You can calculate the probability that an observation is higher, less, or equal to some value, but not the probability that it is exactly equal to some value.
Topics to be discussed include:
From zScores to Normal Probabilities
From Probabilities to zScores to Percentiles
Chapter 5: Summary
You’ll look at fundamental probability models in this session. You will learn the concept of a model's mean or expected value, and how important the normal model is. A discrete probability model is one in which all conceivable outcomes and their probabilities can be counted and listed.
Lesson 9: The Key to Inference: Sampling Distributions
Chapter 1: Introduction
We're ready to bridge the gap between descriptive and inferential statistics and enter the domain of statistical inference now that you've learned about probability and the normal model. You'll learn the basics to moving beyond the sample at hand to make predictions and draw inferences about the overall population in this session.
Chapter 2: Sampling Distributions
In a same way, you can show the distribution of a sample statistic, such as the mean or a proportion. All we need to do now is expand on our prior conversations beyond a single example. Consider what would happen if the sampling process were repeated numerous times and the statistic was determined each time.
Topics to be discussed include:
Simulation of Sampling Distributions
What the Central Limit Theorem Says
How Big is Big Enough?
Chapter 3: Modeling Sample Means
In addition to understanding that the normal distribution may be used to model the mean of a sample, we also need to know the model's mean and standard deviation. We can't calculate probability or utilize the standard model without these numbers.
Topics to be discussed include:
Calculating With the Sampling Distribution of x?
Chapter 4: Modeling Sample Proportions
The normal model can also be used to model the distribution of a sample proportion in this chapter. There will be many parallels to the events in Chapter 3. There are various distinctions in nomenclature and standard deviation, so keep an eye out for these. If you haven't already read how a proportion compares to a mean in the FAQs, you might wish to do so now.
Topics to be discussed include:
Model for the Sample Proportion
Visualizing the Population, Data, and Sampling Distribution of p?
Calculations With the Sampling Distribution of p?
Chapter 5: Summary
You will learn how to transition from describing a specific sample to making conclusions about a whole population in Lesson 9. We start with the concept of a statistic's sample distribution. When you take a sample from a population, you often compute a statistic like the sample mean or sample proportion. If you ran the sample process several times and plotted all of the resulting averages or proportions.
Lesson 10: How Certain Are We? Confidence Intervals for Proportions
Chapter 1: Introduction
In this lesson, you'll learn how to use the margin of error to go from a sample statement like "37 percent of those surveyed agreed with this statement" to a population statement like "We're 95 percent confident that between 35 percent and 39 percent of the population would agree with this statement."
Chapter 2: Estimating With Confidence
In reality, we frequently utilize the point estimate to estimate the associated population parameter as our best guess. This is a population summary number—for example, the proportion of all students who have taken an online class or the average selling price of all residences sold in the area. Keep in mind that in most cases, the demographic parameters are unknown.
Topics to be discussed include:
Confidence Intervals for a Proportion
Margin of Error
Chapter 3: Building Your Confidence in Confidence Intervals
We'll go a little deeper now that you've seen a few confidence intervals and know how to analyze them. We'll go over the technical assumptions and standards that must be met in order for your confidence intervals to be valid. You'll also have additional opportunities to practice calculating and understanding them in a variety of settings.
Topics to be discussed include:
The Necessary Details
Is This Drug Any Better Than a Placebo?
Would You Pay More to Help the Environment?
How Safe is Your Chicken?
Chapter 4: How Large a Sample Do I Need?
It's impossible to predict how someone will respond to a survey or an experiment. The sample size is the one variable that you can control that affects the variability of proportions and the margin of error. Researchers frequently estimate the size sample they'll need when planning a survey or experiment in order to achieve a certain level of precision in their results.
Topics to be discussed include:
Estimating the Sample Size
Sample Size Formula
Planning a Donation Campaign
Planning an Experiment
Chapter 5: Summary
You will see the basics of proportion inference in this lesson. You build the margin of error by starting with the standard error and replacing the unknown population proportion with the sample proportion in the standard deviation formula.
Lesson 11: Trial by Data: Testing Hypotheses About Proportions
Chapter 1: Introduction
You learned how to infer proportions using confidence intervals in the last session. We'll now turn our attention to the other important type of inference: hypothesis tests. Because assertions involving proportions are more prominent in everyday life, we'll start by testing a hypothesis regarding one. Then, in Lesson 12, you'll learn how to test a mean hypothesis.
Chapter 2: Hypothesis Testing Basics
You've seen how statistics starts with a question since the beginning of the course. Usually, you won't be able to answer it readily using information from a book or past knowledge. The data you collect serves as proof for you. You assess the evidence using statistics and probability to test the hypothesis. Formal hypothesis testing are used in this situation.
Topics to be discussed include:
Forming Hypotheses
Test Statistics: Weighing the Evidence
PValues
Drawing a Conclusion
Chapter 3: A Trial by Data: The Reasoning of a Hypothesis Test
At first glance, the logic of hypothesis testing may appear to be backward. You don't come up with a hypothesis and then try to prove it. Instead, you state a null hypothesis (something you don't actually want to prove), assume it's true, and then try to disprove it. This oblique technique is a contradiction proof.
Topics to be discussed include:
How is All This like a Trial by Jury?
Interpreting pValues
Is there really a Home Field Advantage?
Did Advertising Increase Awareness of your Product?
Chapter 4: Hypothesis Testing Details: Assumptions, Conditions, and Possible Errors
We need to go through a few things now that you've seen some hypothesis tests in action. In order for a test's results to be valid, you must consider certain assumptions and criteria, much as you do with confidence intervals. There's always the risk of making the wrong decision when drawing a conclusion from a test.
Topics to be discussed include:
Checking the Assumptions and Conditions
Is there Evidence of Gender Bias in Promotion?
What can Go wrong
Did the events of September 11 Affect the plans of High School Seniors?
Chapter 5: Summary
You will learn the techniques and reasoning processes needed to conduct and analyze a percentage hypothesis test in Lesson 11.
Lesson 12: Inference About Means
Chapter 1: Introduction
We'll look at inference for means now that you've seen how it works for a proportion. Not all data is binary, like "yes or no" or "success or failure." In Lesson 12, you'll learn how to establish confidence intervals for the mean of a quantitative variable and how to test hypotheses for it.
Chapter 2: Building Confidence in the Mean
The sample mean x (xbar) is our best estimation, or point estimate, of the population mean for quantitative data (mu). Even though it's our best estimation, there's only one figure that deviates from the population mean. We'll establish a margin of error around the sample mean, just like we did with proportions, to form an interval that's likely to capture the population mean.
Further Learning
If you want to advance your career once you have achieved your certification, there are many options available. You can further your education with CFS, undertaking another related course such as software engineering, visual design, even the use of Microsoft Excel which is extremely handy to know when dealing with numbers.
You might also opt for a Masters Degree if you find business analysis or marketing analytics has tweaked your interest. The options are endless when you receive a professional education with CFS.
Recognition & Accreditation
Upon successful completion of this course and achieving a passing score for the assessment, you will be issued with an international continuing education credit (CEU) certificate.
This Certificate is applicable worldwide, which demonstrates your commitment to learning new skills. You can share the certificate with your friends, relatives, coworkers, and potential employers. Also, include it in your resume/CV, professional social media profiles and job applications.
Units of Study
There are 12 units of study
What Is Statistics, Anyway?
What's statistics really about? How do you collect reliable data and use it to make informed decisions? In Lesson 1, you'll learn some of the concepts and terms we'll use throughout the course. You'll also find out how statistics affects events in the news and in your everyday life.
Quantitative Data: From Averages to zScores
Once you have a set of data, how can you summarize and interpret it to figure out what it really means? In Lesson 2, you'll learn to summarize data and describe its center along with its variability. As you learn to calculate mean, median, range, and standard deviation, I'll provide examples from different workplaces. You'll see how statistics plays a part in medicine, human resources, education, politics, finance, and marketing.
Displaying Quantitative Data: Dots, Plots, and Histograms
Is there an easier way of understanding data than peering at column after column of numbers? Yes! In Lesson 3, you'll see quantitative data displayed in dot plots, histograms, and many other forms. Knowing how to read and construct these graphs will help you see patterns and spot unusual values in data. Our examples in this lesson come from medicine, mortgage lending, classrooms, biologists' field notes, and the aisles of your local grocery store.
Displaying Qualitative Data: Percentages, Charts, and Graphs
"How much satisfaction do you get from your friendships?" "Would you vote for a qualified woman for president?" "Which mountain in the Himalayas is most dangerous to climb?" In Lesson 4, you'll learn to summarize and display qualitative data from questions like these. We'll focus on charts and tables, and along the way you'll see examples from business, government, and medicine.
Is There a Link? Scatterplots and Correlation
Is there a link between the poverty rate and the crime rate? Is your score on a math exam related to your anxiety level? In Lesson 5, we'll look at relationships between two quantitative variables. You'll learn to make scatterplots and describe what you see. You'll also use correlation to measure the strength of a particular link.
Linear Regression: How Can We Predict the Future?
Can we predict the next worldrecord time in the mile run? How can we forecast CO2 levels in the atmosphere? In Lesson 6, we'll go beyond describing and measuring association between variables. You'll use linear regression to find an equation that models the data. Then you'll use the equation to make predictions.
What's the Chance of That? Probability Concepts
What's the chance you'll have a coin come up "heads" five times in a row? What about drawing four aces from a deck of cards or picking the winning lottery numbers? In Lesson 7, we'll study the basics of probability. You'll learn the rules that govern probability and see how to apply them in a variety of situations.
Probability Models: What's Normal?
What should you expect to happen in a game involving chance? How can you estimate the probability that a healthy baby will be born underweight? In Lesson 8, we'll talk about probability models and expected value. Our focus will be the most common probability model in statistics: the normal model. You'll see this bellshaped distribution in a variety of settings, and you'll learn to use it to estimate probabilities.
The Key to Inference: Sampling Distributions
How can we move beyond the sample at hand to make predictions and draw conclusions about the population? In Lesson 9, you'll discover the key that lets you make inferences about the population. You'll see the most important result in all of statistics—the central limit theorem—and you'll learn why the normal model plays such an important role in statistics. You'll also find out how to use data and probability to evaluate a claim.
How Certain Are We? Confidence Intervals for Proportions
"The margin of error for this poll is plus or minus 3%." What does that mean, anyway? In Lesson 10, we'll begin our journey into statistical inference by focusing on confidence intervals for proportions. You'll learn to calculate the margin of error and use it to build an interval for estimating a population proportion. You'll also see how to estimate the sample size you'd need for a survey.
Trial by Data: Testing Hypotheses About Proportions
Is there really a home team advantage in sports? Did that television ad your company bought result in increased awareness of your product? In Lesson 11, you'll learn to answer questions such as these by testing an appropriate hypothesis using proportions. You'll find out what steps make up a hypothesis test and how you can interpret the results, make inferences, and arrive at informed decisions.
Inference About Means
How do you test hypotheses about means? For example, how can you use a confidence interval to estimate the average number of hours Americans use the Internet each week? In our last lesson together, you'll get an introduction to inference for means. You'll learn to calculate and interpret confidence intervals and hypothesis tests for a mean, and you'll see how to analyze data from a paired experiment. And while we're at it, you'll find out what the history of statistics has to do with the quality of beer in Ireland.
Requirements
Entry requirements
Students must have basic literacy and numeracy skills.
Minimum education
Open entry. Previous schooling and academic achievements are not required for entry into this course.
Computer requirements
Students will need access to a computer and the internet.
Minimum specifications for the computer are:
Windows:
Microsoft Windows XP, or laterModern and up to date Browser (Internet Explorer 8 or later, Firefox, Chrome, Safari)
MAC/iOS
OSX/iOS 6 or laterModern and up to date Browser (Firefox, Chrome, Safari)
All systems
Internet bandwidth of 1Mb or fasterFlash player or a browser with HTML5 video capabilities(Currently Internet Explorer 9, Firefox, Chrome, Safari)
Students will also need access the following applications:
Adobe Acrobat Reader
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study this course, this course is open to anyone who would like to take
this course.
6. What if English is not my first language?
This
course is provided in English, however, due to the digital nature of
our training, you can take your time studying the material and make use
of tools such as google translate and Grammarly.
7. Is this course online or conducted in person?
All our courses are accessible online on any device. You may complete them at your own pace and at your own time.
8. How do I receive my course?
After
you have completed the payment, you will receive a confirmation email
and tax receipt. You will also receive an email containing your course
login details (username and password), as well as instructions on how to
access and log in to your course via the internet with any device,
please check your junk/spam folder in the event that you do not receive
the email.
9. When does this course start?
Providing
you have internet access you can start this course whenever you like,
just go to the login page and insert your username and password and you
can access the online material.
10. What is online learning like?
Online learning is easy, if not easier than a traditional academic situation.
By studying an online course, the usual boundaries caused by location and time constraints are eliminated, meaning you are free to study where and when you want at your own pace.
Of course, you will need to be able to selfmanage your time and be organized, but with our help, you’ll soon find yourself settling into a comfortable rhythm of study.
11. What computer skills do I need for my course?
You
don't need to be a computer expert to succeed with our online training,
but you should be comfortable typing, using the internet and be capable
of using common software (such as Microsoft word).
12. How long will you have access to the online course?
The majority of our courses have unlimited lifetime access, meaning you can access this course whenever you want.
Please also check the course summary, as a small selection of courses have limited access.
13. How long will my course take?
Course duration, is listed under Course Summary
14. Do I need to buy textbooks?
All the required material for your course is included in the online system, you do not need to buy anything else.
15. Is the course interactive?
Yes, all our courses are interactive.
16. Is there an assessment or exam?
Yes,
you will be required to complete a multiplechoice test online at the
end of your course, you can do this test as many times as you require.
17. What type of certificate will I receive?
You
will receive a Certificate of Completion that is applicable worldwide,
which demonstrates your commitment to learning new skills. You can share
the certificate with your friends, relatives, coworkers and employers.
Also, include it in your resume/CV, professional social media profiles
and job applications.
Wendy Sue Hunt  5 STAR REVIEW
"If you are considering taking any “Courses for Success”, I would highly recommend it. I have always been a firm believer it’s important to always sharpen your skills. You are never too old to learn more. I found the courses very helpful, interesting and easy to understand.
The term “Courses for Success” helped me in my current position to succeed. After completing the courses, I gave my manager the completion certificates. Recently I received a promotion too."
Valencia Marie Aviles  5 STAR REVIEW
"I
had a very good experience with my course. It has helped me to get
multiple jobs and prepared me for almost everything I would need to
know. The course was very informative and easy to understand and broken
up perfectly to be done in a short amount of time while still learning a
good amount! I would recommend Courses for Success to anyone trying to
get abs certifications for job advancements, it is well worth it!"
ELENA GRIFFIN  5 STAR REVIEW
"I have absolutely enjoyed the materials from Courses for Success. The materials are easy to understand which makes learning enjoyable. Courses for Success have great topics of interest which make you come back for
more.
Thank you Courses for Success for being part of my learning journey and making education affordable!"
Our
completion certificates are very valuable and will help you progress in
your work environment and show employers how committed you are to learn
new skills, you might even get a promotion.
18. Will this course be credited by universities?
No, it is not equivalent to a college or university credit.
19. Am I guaranteed to get a job with this certificate?
This course will give you the skills you need to help you obtain employment, but it’s up to you if you get the job or not.
20. How will this course assist me with my career?
Studying
and completing this course will show employers that you have the
knowledge in this field, additionally you will gain more confidence in
this area of expertise.
21. How long is the certificate valid for?
The Certificates are valid for life and do not need renewing.
22. Can I take more than one course at a time?
Courses
are studied online at your own pace and you are free to study as many
or as few courses as you wish, we also offer online course bundles that
allow you to save on additional courses so that you may get all the
topics related to your training goals in one go.
23. What are the Payment Methods available? Is there a payment plan?
We accept payments via PayPal, Credit Card and Bank Transfer.
Payment Plans: We have partnered with Partial.ly, to offer our own in house payment plan. Everyone is PreApproved, providing the initial deposit is paid in full.
To pay via bank transfer contact us info@coursesforsuccess.com
24. Can I purchase for multiple people?
Yes, you can do this by purchasing individually via website or send us a request via email at info@coursesforsuccess.com
25. Can I request for an invoice before purchase?
Yes, you can request for an invoice via email at info@coursesforsuccess.com
26. Purchase for a gift?
Yes, you can purchase this course as a gift, simply send an email to info@coursesforsuccess.com, with the course details and we can accommodate this.
27. Can I create my own course bundle?
Yes,
you can customize your own bundle. Please send us the complete list
with the exact course link of the courses you'd like to bundle up via
email info@coursesforsuccess.com and we will create them for you. *Each course access, time of completion and certification varies depending on the course type.
28. How will I contact Courses For Success if I have any questions?
You can contact our support team, at any time through live chat on our website, or email at info@coursesforsuccess.com, or by calling one of our phone numbers depending on which country you are in.
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Training Packages
Looking for specific training for yourself or employees in your Business. We can provide tailormade Training Packages.
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