Hi i need help with this benchmark i have done some of the calulations but not sure if they are right.

Relationship of Height and WeightUsing the given Height and Weight data set, follow the steps in the weekly video or on pages 584-585 of the textbook for performing a regression analysis using Excel to analyze the Height and Weight Data set (assume height is the input variable x and weight is the output variable y).Once you have performed the analysis in Excel, state the correct simple linear regression equation and use the regression equation to predict the weight (in pounds) of a person who is 65 inches tall and the weight (in pounds) of a person who is 100 inches tall.Why might the regression equation you have found not be a good predication of the weight of someone who is 100 inches tall?

Progress CheckUse this activity to assess whether you and your peers can: If conditions are met, use the ANOVA F-test to examine the relationship between a categorical explanatory variable that has more than two values and a quantitative response variable.State the conclusion of an ANOVA F-test in context.Learn by DoingThe purpose of this activity is to give you guided practice in carrying out the ANOVA F-test using StatCrunch.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.Use the rubric at the bottom of this page as a guide for completing this assignment.A list of StatCrunch directions is provided after the Prompt section below.DirectionsSubmit your work:Carefully read all sections below (beginning with the Context section and ending with the Prompt section).Commit a good-faith effort to address all items in the Prompt section below. Please be sure to number your responses.If directed to do so, embed all required StatCrunch output in your initial submission. Please do not submit StatCrunch output as an attachment.Complete your assigned peer reviews:After you submit your initial good-faith attempt, continue to the ANSWER(S) page and review your instructor's response. But please do not submit your corrected work yet.Within three days after the due date, return to this assignment and complete your assigned peer reviews (directions (Links to an external site.)).Submit your corrected work:We all learn from mistakes (our own and our classmates' mistakes). So please do not immediately correct your own mistakes. If possible, wait until you receive feedback from at least one of your peers. If necessary, correct your work and resubmit the entire assignment - including any required StatCrunch output. Your instructor will only review and grade your most recent submission, so please do not refer to a previous submission.ContextCritical flicker frequency (CFF) and eye colorComputer screens and fluorescent bulbs flicker. If the frequency of the flicker is below a certain threshold, the eye detects the flicker, and it is annoying!Different people have different flicker "threshold" frequencies (known as the critical flicker frequency, or CFF). The mean critical threshold frequency is important for product manufacturing as well as tests for ocular disease.In 1973, researchers conducted a study to answer the following question.Research question: Do people with different eye color have different threshold flicker sensitivity?The 1973 study ("The Effect of Iris Color on Critical Flicker Frequency," Journal of General Psychology [1973], 91–95) obtained the following data from a random sample of 19 subjects.ColorThresholdFrequency (CFF)BlueBrownGreen Brown 26.825.726.826.4 Brown 27.927.227.924.2 Brown 23.729.923.728 Brown 25.028.52526.9 Brown 26.329.426.329.1 Brown 24.828.324.8 Brown 25.725.7 Brown 24.524.5 Green 26.4 Green 24.2 Green 28.0 Green 26.9 Green 29.1 Blue 25.7 Blue 27.2 Blue 29.9 Blue 28.5 Blue 29.4 Blue 28.3In this spreadsheet the data is presented in two formats.Stacked data: The quantitative data is stacked in one column. The first two columns show the data in a stacked format. Each variable is a column (one column for the explanatory variable eye color; one column for the response variable CFF) and each row is an individual. For example, the first row is a brown-eyed person with a CFF of 26.8.Unstacked data: The quantitative data is distributed across the groups in multiple columns. The last three columns show the same data in an unstacked format. In this format, each column is a group defined by a value of the explanatory variable: one column for blue-eyed people, one column for brown-eyed people and one column for green-eyed people. Each column contains the response values (CFF) for that group.The format of the data in the spreadsheet affects how we use StatCrunch to analyze it.VariablesColor: This is the explanatory variable. The categorical data represents the groups we will compare.CFF (flicker threshold sensitivity): This is the response variable. The quantitative data represents the frequency threshold at which the subject sees the flicker.DataDownload the flicker (Links to an external site.) datafile. As always, ignore or close any prompt that invites you to login while downloading the file. Upload the datafile to StatCrunch.PromptWe will conduct an ANOVA F-test for the variables Colorand CFF. The flicker datafile is available in the Data section below. Also, the StatCrunch directions are provided in the list a the bottom of this page.What are the hypotheses for the ANOVA test? Be sure that you define clearly the parameters.Are the conditions that allow us to safely use the ANOVA F-test met? Explain.Note: To verify conditions, you will need to examine the distribution of CFF scores for each sample (because the samples are small).Use StatCrunch to create side-by-side dotplots, histograms or boxplots (your choice) to examine the distribution of CFF scores for each sample. You can use either data format; choose one (stacked data in the first two columns; or unstacked data in the the last three columns). To create the side-by-side graphs (for either data format) see the list of StatCrunch directions below. Download the StatCrunch output window (your graph), upload it to your Stats-Classfolder, and then embed the .png file (your graph) in your initial post. To recall how to complete these tasks, see the list of StatCrunch directions below.You will also need to compare the sample standard deviations. Use StatCrunch to find the summary statistics, means and standard deviations for the comparison groups (select the the appropriate Descriptive Statistics StatCrunch directions from the list below). Then copy and paste the table into your initial post and explain how the rule of thumb for comparing standard deviations is met.Use StatCrunch to carry out the ANOVA F-test (select the appropriate ANOVA StatCrunch directions from the following two options). Anova F-test Stacked Data Format ORAnova F-test Unstacked Data FormatCopy and paste the output table into your initial post.State your conclusion in context of eye color and mean CFF.List of StatCrunch DirectionsEach link will open in a new window. To return to this discussion, either close the new tab or select the tab for this discussion. Purchase StatCrunch (You only need to do this once.)Open StatCrunchDownload Excel Data FileUpload Excel Data File to StatCrunchDownload StatCrunch Output Window (no screenshots; please use these directions)Upload Files into Your Stat-Class Folder in CanvasEmbed Pictures in a Discussion Post (no attachments; please use these directions)Side-by-side Boxplots Stacked Data FormatSide-by-side Boxplots Unstacked Data FormatSide-by-side Dotplots Stacked Data FormatSide-by-side Dotplots Unstacked Data FormatSide-by-side Histograms Stacked Data FormatSide-by-side Histograms Unstacked Data FormatDescriptive Statistics Multiple Categories Stacked Data FormatDescriptive Statistics Multiple Categories Unstacked Data FormatCopy & Paste a StatCrunch TableAnova F-test Stacked Data FormatAnova F-test Unstacked Data FormatRubricPeer Reviewed Assignment w/ StatCrunchPeer Reviewed Assignment w/ StatCrunchCriteriaRatingsPtsThis criterion is linked to a Learning OutcomeAddressing the Prompt6 ptsFull MarksAll parts of the Prompt are addressed. Answers are correct. Statistical vocabulary is used appropriately. Writing is clear and thought process is easy to follow.4 ptsPartial CreditSome parts of the prompt are not addressed, are incorrect, or are unclear.0 ptsNo MarksThe prompt is not addressed.6 ptsThis criterion is linked to a Learning OutcomeStatCrunch Data2 ptsFull MarksAppropriate StatCrunch graphs and/or tables are provided as directed.1 ptsPartial CreditStatCrunch graphs and tables are inappropriate or missing important information.0 ptsNo MarksNo StatCrunch information is provided.2 ptsThis criterion is linked to a Learning OutcomeIndividual Penalty0 ptsNo individual penalty-1 ptsIndividual penalty.Please see the instructor comments for more information.0 ptsThis criterion is linked to a Learning OutcomePeer Reviews2 ptsFull MarksYou completed all assigned peer reviews (maximum of 2). For each peer review, the points you assigned in the rubric are appropriate. You included comments explaining the score you posted in the rubric. If you deducted points in the rubric, your comments explain what the author needs to do to earn a higher grade when the teacher grades the assignment.1 ptsPartial CreditCommitted a good-faith effort to provide a high-quality peer review, but many necessary instructive comments are missing.0 ptsNo MarksNo peer review provided or the comments are not instructive.2 ptsTotal Points: 10