- Course type: Self-paced
- Available Lessons: 111
- Average Lesson Length: 8 min
Eligible for Certificate:
Certificates show that you have completed the course. They do not provide credit.
Watch a preview:chapter 1 / lesson 1Descriptive & Inferential Statistics: Definition, Differences & Examples
Course SummaryIncrease your statistical analysis skills and earn an Introduction to Statistics Certificate with this fun course. Watch short video lessons and take quizzes to prepare for a final exam to get a certificate you may be able to use to fulfill continuing education credits.
To Start This Course Today
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Course Practice TestCheck your knowledge of this course with a 50-question practice test.
- Comprehensive test covering all topics
- Detailed video explanations for wrong answers
About This Course
The concise and engaging video lessons in this course can help you earn an Introduction to Statistics Certificate in as little as two weeks. On-screen graphics and dynamic animations make it easy to remember key statistical processes, such as calculating the mean or median, determining probability of simple events and interpreting confidence intervals.
Who's This For?
Financial professionals, business analysts, actuaries and anyone who wants to refresh their statistical analysis skills can take this course.
No prerequisites are needed for this course.
Benefits of the Certificate
You'll be able to benefit from this course in your personal life and career:
- Include this certificate on your LinkedIn profile or resume to showcase your mastery of statistical analysis and probability concepts, which might be of interest to current and future employers.
- Potentially fulfill continuing education requirements with this course.
- Use the statistical analysis methods you learn in this course to determine the expected return rate for a mutual fund or to figure out your average fuel usage over a certain period of time.
Introduction to Statistics Program Breakdown
This certificate course includes ten chapters covering data summarization, probability, hypothesis testing and more.
Overview of Statistics
This chapter introduces you to populations and samples, quantitative and categorical data, random selection and experiments. You'll learn about bias and confounding, convenience sampling and data gathering methods.
Learn to calculate mean, median and mode before moving on to study a data set's maximums and minimums, quartiles, interquartile range and standard deviation. You'll also learn to find percentiles in a data set, determine the variance and rank data.
Tables and Plots
In this chapter, study frequency, relative frequency and cumulative frequency tables. Learn to calculate percent increase, and find out how to create stem and leaf displays, histograms, dot plots and two-way tables. Discover the uses of univariate and bivariate data.
This chapter teaches you to find the probability of simple, compound and complementary events as well as independent and dependent events. You'll learn to calculate conditional probabilities, permutations and the probability of permutations.
Discrete Probability Distributions
Learn to develop discrete probability distributions and find expected values in games of chance. This chapter also shows you how to find binomial probabilities using formulas and tables.
Continuous Probability Distributions
Discover how to find z-scores, estimate areas under a curve and use normal distribution. You'll also graph probability distributions and solve problems using continuous probability.
This chapter provides instruction on simple, stratified, systematic and cluster random samples. You'll learn about sampling distributions, the central limit theorem and the law of large numbers.
Find out how to calculate confidence intervals, determine a sample size and use the t distribution in this chapter.
This chapter teaches you to conduct hypothesis tests for large and small independent samples, matched pairs and proportions. You'll also find out about type I and type II errors as well as effect sizes.
Regression & Correlation
Learn to create scatterplots and interpret the correlation coefficient or slope and intercept of a linear model. This chapter also teaches you to transform non-linear data and find the coefficient of determination.
Earning College Credit
Did you know… We have over 160 college courses that prepare you to earn credit by exam that is accepted by over 1,500 colleges and universities. You can test out of the first two years of college and save thousands off your degree. Anyone can earn credit-by-exam regardless of age or education level.
To learn more, visit our Earning Credit Page
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