Significance Testing
Topic Review on "Title": 
5 Steps of Hypothesis Testing
 Step1: H0: (null hypothesis)
 Step 2: Ha: (The alternative hypothesis)
 Step 3: The test statistic and its pvalue:
 Step 4: The critical value and its rejection region
 Step 5: Conclusion: Reject H0 or Do not reject H0
 How do you decide when to reject H0?
 You need to set a significance level, (e.g., 01 or .05) that represent the maximum risk you can tolerate to have when making a mistake of rejecting H0.
 Then compare that significance level a with pvalue or, compare the statistics with critical value.
Hypothesis Test of a Population Mean
 Suppose We take a random sample
 n >= 30 from a population with mean m and
 standard deviation s. s is known (s » since n is large)
 We write the hypothesis test as:
Twotailed:
Onetailed:
Test statistics
Pvalue and Critical Value approaches
 pvalue:
 A pvalue is a measure of how much evidence we have against the null hypotheses. The smaller the pvalue, the more evidence we have against H0. If pvalue< a (significance level), reject H0.
Pvalue and critical approach are equivalent
 If the pvalue <a, reject H0. Conclude that the results are statistically significant at level a.
 If the pvalue > a, do not reject H0. Conclude that the results are not significant at level.
 If test statistic > critical value, reject H0.
 If test statistic < critical value, do not reject H0.
Two Types of error
 Define:
 a = P(Type I error) = P(reject H0  H0 is true)
 b = P(Type II error) = P( do not reject H0  H0 is false)
 Our goal is to keep a, b as small as possible.

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"Title" Tutorial Summary : 
Significance testing is covered in this tutorial. Detailed description of steps in hypothesis testing is presented along with illustrative examples to guide you through the testing processes to final conclusion.
By completing this course, you will learn about the significance testing (hypothesis testing), including introduction to hypothesis testing, twotailed hypothesis testing, onetailed hypothesis testing, hypothesis testing for one population mean, difference between two population means, one population proportion and difference between two population proportions

Tutorial Features: 
Specific Tutorial Features:
 Step by step examples showing all details about significance testing are presented.
 Examples throughout the tutorial facilitate the understanding of many different types of hypothesis testing.
Series Features:
 Concept map showing interconnections of new concepts in this tutorial and those previously introduced.
 Definition slides introduce terms as they are needed.
 Visual representation of concepts
 Animated examples—worked out step by step
 A concise summary is given at the conclusion of the tutorial.

"Title" Topic List: 
 Introduction to hypothesis testing
 Twotailed hypothesis testing
 Onetailed hypothesis testing
 Hypothesis Testing for
 One Population Mean
 Difference Between Two Population Means
 One Population Proportion
 Difference Between Two Population Proportions

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