Hi i have an assignment to submit and I am uploading the template needed to complete the assignment. The template information will be replaced with the answers you supply. The document is called DAA Template. I am pasting the information for Assignment 8 in the requirements area. SPSS is needed to open the grades file and to complete this assignment. I have attached the attachment that includes all resources needed. Thank you so muchAssignment 8[u08a1] Unit 8 Assignment 1t TestsSee the Resources area for links to resources that you will use for this assignment:You will complete this assignment using the DAA Template.Read the SPSS Data Analysis Report Guidelines for a more complete understanding of the DAA Template and how to format and organize your assignment.Refer to the IBM SPSS Step-By-Step Guide: t Tests for additional information on using SPSS for this assignment.If necessary, review the Copy/Export Output Instructions to refresh your memory on how to perform these tasks. As with your previous assignments, your submission should be in narrative format with supporting statistical output (table and graphs) integrated into the narrative in the appropriate places (not all at the end of the document).You will analyze the following variables in the grades.sav data set:gendergpaStep 1: Write Section 1 of the DAA.Provide the context of the grades.sav data set.Include a definition of the specified variables (predictor, outcome) and corresponding scales of measurement.Specify the sample size of the data set.Step 2: Write Section 2 of the DAA.Analyze the assumptions of the t test.Paste the SPSS histogram output for gpa and discuss your visual interpretations.Paste SPSS descriptives output showing skewness and kurtosis values for gpa and interpret them.Paste SPSS output for the Shapiro-Wilk test of gpa and interpret it.Report the results of the Levene test and interpret it.Summarize whether or not the assumptions of the t test are met.Step 3: Write Section 3 of the DAA.Specify a research question related to gender and gpa.Articulate the null hypothesis and alternative hypothesis.Specify the alpha level.Step 4: Write Section 4 of the DAA.Paste the SPSS output of the t test.Report the results of the SPSS output using proper APA guidelines (refer to the Unit 8 Introduction and the "Results" example from the Warner text in Chapter 5). Include the following:t.Degrees of freedom.p value.Effect size.Interpretation of effect size.Means and standard deviations for each group.Mean difference.95% confidence interval of the difference of sample means.Interpret the results against the null hypothesis.Step 5: Write Section 5 of the DAA.Discuss the implications of this t test as it relates to the research question.Conclude with an analysis of the strengths and limitations of the t test.Submit your DAA Template as an attached Word document in the assignment area.Resourcest Tests Scoring Guide.IBM SPSS Step-by-Step Guide: t Tests [DOC].DAA Template [DOCX].APA Style and Format.SPSS Data Analysis Report Guidelines.Copy/Export Output Instructions.

Learn by DoingMatched Pairs: In this lab you will learn how to conduct a matched pairs T-test for a population mean using StatCrunch. We will work with a data set that has historical importance in the development of the T-test.Paired T hypothesis test: μD = μ1 - μ2 : Mean of the difference between Regular seed and Kiln-dried seed H0 : μD = 0 HA : μD > 0 Hypothesis test results: Difference Mean Std. Err. DF T-Stat P-value Regular seed - Kiln-dried seed -33.727273 19.951346 10 -1.6904761 0.9391 Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.Here are the directions, grading rubric, and definition of high-quality feedback for the Learn by Doing discussion board exercises.A list of StatCrunch directions is provided at the bottom of this page.ContextGosset's Seed Plot DataWilliam S. Gosset was employed by the Guinness brewing company of Dublin. Sample sizes available for experimentation in brewing were necessarily small. At that time, Gosset contacted a famous statistician Karl Pearson (1857-1936) and was told that there were no techniques for developing probability models for small data sets. Gosset studied under Pearson, and the outcome of his study was perhaps the most famous paper in statistical literature, "The Probable Error of a Mean" (1908), which introduced the T-distribution.Since Gosset was employed by Guinness, any work he produced would be owned by Guinness, so he published under a pseudonym, "Student"; hence, the T-distribution is often referred to as Student's T-distribution.To illustrate his analysis, Gosset used the results of seeding 11 different plots of land with two different types of seed: regular and kiln-dried. He wanted to determine if drying seeds before planting increased plant yield. Since different plots of soil may be naturally more fertile, this confounding variable was eliminated by using the matched pairs design and planting both types of seed in all 11 plots.The resulting data (corn yield in pounds per acre) are as follows. Plot Regular seed Kiln-dried Seed 1 1903 2009 2 1935 1915 3 1910 2011 4 2496 2463 5 2108 2180 6 1961 1925 7 2060 2122 8 1444 1482 9 1612 1542 10 1316 1443 11 1511 1535 We use these data to test the hypothesis that kiln-dried seed yields more corn than regular seed.Because of the nature of the experimental design (matched pairs), we are testing the difference in yield. Plot Regular seed Kiln-dried Seed Difference 1 1903 2009 –106 2 1935 1915 20 3 1910 2011 –101 4 2496 2463 33 5 2108 2180 –72 6 1961 1925 36 7 2060 2122 –62 8 1444 1482 –38 9 1612 1542 70 10 1316 1443 –127 11 1511 1535 –24 Note that the differences were calculated: regular − kiln-dried.VariablesRegular seed: regular seeds that were traditionally used for planting kiln-dried: seed that were kiln-dried before plantingDataDownload the seed (Links to an external site.) data file, and then upload the file into StatCrunch.PromptState the hypotheses and define the parameter.Checking conditions: Since Gosset invented the T-distribution, we will assume that his sample meets the conditions and proceed with the T-test. Regardless, answer these questions to demonstrate your understanding of the conditions for use of the T-model. But first you will need to review the dotplots for the data (opens in a new tab). Which graph is used to check conditions? Why?What do we look for in the graph to verify that conditions are met?What else do we need to know about the sample of seeds before using the T-test? Use StatCrunch to find the T-score and the P-value. Hint: as you work through the StatCrunch directions, keep in mind that we want to calculate the differences as regular − kiln-dried . So you will choose Regular seed for Sample 1 and kiln-dried seed for Sample 2. (directions) Copy and paste the information in the StatCrunch output window into your initial post.State a conclusion based on the context of this scenario.EXAMPLE TO RIGHT ANSWER1. Ho: μ=0Ha: μ>0The average difference is -33.732. a) We use the graph of the differences because that is what we are analyzing.b) We look to see if the graph is normally distributed, not skewed, and doesn't have outliers.c) We don't know if the data is randomly selected.3.Paired T hypothesis test: μD = μ1 - μ2 : Mean of the difference between Regular seed and Kiln-dried seed H0 : μD = 0 HA : μD > 0 Hypothesis test results: Difference Mean Std. Err. DF T-Stat P-value Regular seed - Kiln-dried seed -33.727273 19.951346 10 -1.6904761 0.9391 Differences stored in column, Differences.4. Based on the P-value of 0.9391, we do not have enough evidence to reject the null hypothesis. There is no statistically significant evidence to show that kiln-dried seeds yield more than regular seeds.