PSYCH 203 1st Edition Lecture 19Outline of Last Lecture I. Introduce 4 stages of Null hypothesis significance testing II. Define Type 1 and Type 2 errors III. Describe File Drawer Problem IV. Identify limitations of p-values Outline of Current Lecture I. How to turn observed data into a p-valueII. Famous 8 Steps a. State the hypothesesb. Set the alphac. Select the appropriate inferential test statistic d. Use the selected inferential test to compute a test statistic. The test statistic is a single number that comes from the formula for the specific test. These test statistics can be used to compute p- values.e. Determine the critical value for the test statistic. this is the minimum value needed to reject the null hypothesis. in other words, this is the value needed to reject the null.f. Compare your obtained test statistic to the critical value.g. If the obtained value is bigger than the critical value, Reject the Null Hypothesish. If the obtained value is smaller than the critical value, Fail to Reject the null hypothesisIII. One sample z-test a. When to use the testb. Procedure c. Calculate the Standard Error of the Mean (SEM)These notes represent a detailed interpretation of the professor’s lecture. GradeBuddy is best used as a supplement to your own notes, not as a substitute.Current LectureI. How to turn observed data into a p-valueII. Famous 8 Steps a. State the hypothesesi. 1. State the null and research hypotheses – H0: μAP = μGPii. In words: There is no difference in the average fitness of children in athletic programs and children in general.iii. H1: xbarAP > μGPiv. In Words: The average fitness of children in our athletic program is greater than the average fitness levels of children in general.b. Set the alphai. The level of risk associated with the null 1. Use .05 in this class c. Select the appropriate inferential test statistic i. Right now you can only choose the one sample z test d. Use the selected inferential test to compute a test statistic. The test statistic is a single number that comes from the formula for the specific test. These test statistics can be used to compute p- values.i. SPSS provides exact p-values. Hand calculations are rarely as precise e. Determine the critical value for the test statistic. this is the minimum value needed to reject the null hypothesis. in other words, this is the value needed to reject the null.i. 1.96 or -1.96f. Compare your obtained test statistic to the critical value.i. Test Statistic/Obtained Value = 5.67 – Critical Value = -1.96 and 1.96– Obtained Statistic is larger than 1.96!g. If the obtained value is bigger than the critical value, Reject the Null Hypothesisi. When the obtained value is bigger than your critical value, your p-value is smaller than your cutoff.h. If the obtained value is smaller than the critical value, Fail to Reject the null hypothesisi. This means your p-value is bigger than your cutoffIII. One Sample z-test a. Learn when to use testi. When we want to test the difference between a sample mean and the population mean 1. Ex: is the average depression score from this sample different from the population?b. Learn the Procedurei. You need:1. Population Dataa. Mean b. Standard deviation2. Sample dataa. Mean b. Sample size 3. Formula: z= (xbar-μ)/SEM4. SEM= σ/ √na. Remember that σ = standard deviation for the population b. n= sample size c. Calculate the Standard Error of the Mean (SEM)i. There will often be some difference or "error" between sample means and μ. Some sample means will be relatively close to μ and others will be relatively far away.ii. The standard error of the mean is a fancy phrase for the standard deviation of sample means; This value is the typical distance between Mand