Statistical & Hypothesis Tests: Getting Started with Hypothesis Testing
Statistics
| Intermediate
- 9 Videos | 52m 4s
- Includes Assessment
- Earns a Badge
Hypothesis testing is the bedrock of inferential statistics, allowing us to draw inferences reliably about the population as a whole. Use this course to learn more about the distinction between descriptive and inferential statistics and how the latter seek to generalize from the sample to the population as a whole. Examine the components of a typical hypothesis test, such as the null and alternative hypothesis, the test statistic, and the p-value. You'll also explore type-I and type-II errors and the use cases and conceptual underpinnings of t-tests and ANOVA. By the time you finish this course, you will be able to identify use-cases for hypothesis testing and conceptually construct the appropriate null and alternative hypotheses for such tests.
WHAT YOU WILL LEARN
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discover the key concepts covered in this courseoutline how descriptive and inferential statistics workdescribe the fundamentals of hypothesis testingset up null and alternative hypotheses for statistical testsinterpret p-values using alpha levels
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explore the one-sample, two-sample, and paired-sample T-testscompare and contrast type I and type II errors in hypothesis testingapply the ANOVA test for multiple groupssummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 42sUP NEXT
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2.Introducing Statistics7m 43s
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3.Introducing Hypothesis Testing2m 37s
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4.The Null Hypothesis and the Alternative Hypothesis9m 4s
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5.P-values and Alpha Levels10m 13s
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6.Introducing T-tests7m 43s
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7.Errors in Hypothesis Testing4m 57s
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8.Performing ANOVA Analysis5m 37s
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9.Course Summary2m 28s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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