Analyze cases of Type I and Type II errors.

Assignment: z Scores Hypothesis Testing

Permalink: https://nursingpaperslayers.com/assignment-z-sco…pothesis-testing/
Assignment: z Scores, Type I and II Errors, Hypothesis Testing
This is your second IBM SPSS assignment. It includes three sections in which you will:

Generate z scores for a variable in grades.sav and report and interpret them.
Analyze cases of Type I and Type II errors.
Analyze cases to either reject or not reject a null hypothesis.
Download the Unit 4 Assignment 1 Answer Template from the Resources area and use the template to complete the following sections:

Section 1: z Scores in SPSS.
Section 2: Case Studies of Type I and Type II Errors.
Section 3: Case Studies of Null Hypothesis Testing.
Format your answers in narrative style, integrating supporting statistical output (table and graphs) into the narrative in the appropriate places (not all at the end of the document). See the Copy/Export Output Instructions in the Resources area for assistance.

Submit your answer template as an attached Word document in the assignment area.

Resources
z Scores, Type I and II Errors, Hypothesis Testing Scoring Guide.
Copy/Export Output Instructions.
Unit 4 Assignment 1 Answer Template.
APA Style and Format
The decision rule is based on specific values of thetest statistic (e.g., reject H0 if Z > 1.645). The decision rule for a specific test depends on 3 factors: the research or alternative hypothesis, the test statistic and the level of significance.

To find the Z score of a sample, you’ll need to find the mean, variance and standard deviation of the sample. To calculate the z–score, you will find the difference between a value in the sample and the mean, and divide it by the standard deviation.

Simply put, a z–score is the number of standard deviations from the mean a data point is. But more technically it’s a measure of how many standard deviations below or above the population mean a raw score is. A z–score is also known as a standardscore and it can be placed on a normal distribution curve.

Order