ATTACHMENT FILE: Activity 4c.sav Attachment: Activity 4c.sav.sav Part C All of us have had our blood pressure measured while at our physician's office. How accurate are these measurements? It may surprise you to learn that there is something called \"white coat syndrome\"the tendency of some people to exhibit elevated blood pressure in clinical (medical) settings only. In other words, for these people the very fact that the physician is taking their blood pressure causes it to increase (for more information about white coat syndrome see http://www.webmd.com/anxietypanic/features/beyondwhitecoatsyndrome). In this section, you will be using the \"Activity 4c.sav\" data file to determine whether you find support for the existence of white coat syndrome. In this study, 60 participants were randomly assigned to one of three groups. The \"settings\" variable indicates the location in which the participants' blood pressure was recorded: 1=home, 2=in a doctor's office, and 3=in a classroom setting. The \"SystolicBP\" variable contains the participants' systolic pressure (the \"upper\" number). The \"DiastolicBP\" variable contains the participant's diastolic pressure (the \"lower\" number). 1. Exploratory Data Analysis/Hypotheses. a. Perform exploratory data analysis on both the SystolicBP and DiastolicBP variables. Using SPSS, calculate the mean and standard deviation of these two variables. Be sure that your analysis is broken down by setting (e.g., you will have six means, six SD's, etc.). b. Create two graphsone for systolic and one for diastolic pressure. Each graph should clearly delineate the three groups. c. Write a null and alternative hypothesis for the comparison of the three groups (note that your hypothesis will state that the three groups are equivalent; be sure to word your null hypothesis correctly). 2. ANOVA. a. Using the \"Activity 4c.sav\" data file, perform two single factor ANOVAs: one using SystolicBP and one using DiastolicBP as the dependent variable. b. If appropriate for either or both of the ANOVAs, perform post hoc analyses to determine which groups actually differ. c. Write one paragraph for each ANOVA (be sure to use APA style). At a bare minimum, each paragraph should contain the three means, three SD's, ANOVA results (F, df), post hoc tests (if applicable), effect size, and an interpretation of these results. LINK TO DATA SET Activity 5.sav Attachment: Activity 5.sav.sav Complete the following: Use an existing dataset to compute a factorial ANOVA. All SPSS output should be pasted into your document. The \"Activity 5a.sav\" file contains a dataset of a researcher interested in finding the best way to educate elementary age children in mathematics. In particular, she thinks that 5th grade girls do better in small class sizes while boys excel in larger classes. Through the school district, she has arranged a pilot program in which some classroom sizes are reduced prior to the statewide mathematics competency assessment. In the dataset, you will find the following variables: Participant: unique identifier Gender: Male (M) or Female (F) Classroom: Small (1) - no more than 10 children Medium (2) - between 11 and 19 children Large (3) - 20 or more students Score - final score on the statewide competency assessment. Complete the following: 1. Exploratory Data Analysis. a. Perform exploratory data analysis on all variables in the data set. Realizing that you have six groups, be sure that your exploratory analysis is broken down by group. When possible, include appropriate graphs to help illustrate the dataset. b. Give a one to two paragraph write up of the data once you have done this. c. Create an APA style table that presents descriptive statistics for the sample. 2. Factorial ANOVA. Perform a factorial ANOVA using the \"Activity 5a.sav\" data set. a. Is there a main effect of gender? If so, explain the effect. Use post hoc tests when necessary (or explain why they are not required in this specific case). b. Is there a main effect of classroom size? If so, explain the effect. Use post hoc tests when necessary (or explain why they are not required in this specific case). c. Is there an interaction between your two variables? If so, using post hoc tests, describe these differences. d. Is there support for the researcher's hypothesis that girls would do better than boys in classrooms with fewer students? Explain your answer. e. Write up the results in APA style and interpret them. Be sure that you discuss both main effects and the presence/absence of an interaction between the two. Link to data Activity 5.sav Attachment: Activity 5.sav.sav $FL2@(#) IBM SPSS STATISTICS DATA FILE 64-bit MS Windows 20.0.0 ################<#########Y@17 Sep 1218:30:37 ###########################PARTICIP########################GENDER ####Gender ########################CLASSROO####Classroom size ########################MATH_SCO########F #Female M #Male ##########################? 10 or less #######@#11-19 #######@ 20 or more ##########################################################################        ############ ####################################################### #######I###PARTICIP=Participant GENDER=Gender CLASSROO=Classroom MATH_SCO=Math_Score########################<###################[###Participant: $@Role('0' )/Gender:$@Role('0' )/Classroom:$@Role('0' )/Math_Score:$@Role('0' )############ ###windows-1252#######eefeM M iejeM M keleM ofpfM M qfrfM ufvfM M wfxfM {g|gM M }g~gM ggM M eeF eeF F eeF ffF F f#fF ffF F ffF ggF F ggF ggF F M M M M F F F geheM M meneM M sftfM M ygzgM M ggM M e#eF F eeF F ffF F F ggF F F ggF F Link to data set: Activity 5.sav Attachment: Activity 5.sav.sav Create an MS Word document by cutting and pasting SPSS output into the document. Name the file in the following format: lastnamefirstinitialEDU8006-5.doc (example: smithbEDU80065A.doc). Complete the following: Use an existing dataset to compute a factorial ANOVA. All SPSS output should be pasted into your document. The \"Activity 5a.sav\" file contains a dataset of a researcher interested in finding the best way to educate elementary age children in mathematics. In particular, she thinks that 5th grade girls do better in small class sizes while boys excel in larger classes. Through the school district, she has arranged a pilot program in which some classroom sizes are reduced prior to the state-wide mathematics competency assessment. In the dataset, you will find the following variables: Participant: unique identifier Gender: Male (M) or Female (F) Classroom: Small (1) - no more than 10 children Medium (2) - between 11 and 19 children Large (3) - 20 or more students Score - final score on the statewide competency assessment. Complete the following: 1. Exploratory Data Analysis. a. Perform exploratory data analysis on all variables in the data set. Realizing that you have six groups, be sure that your exploratory analysis is broken down by group. When possible, include appropriate graphs to help illustrate the dataset. b. Give a one to two paragraph write up of the data once you have done this. c. Create an APA style table that presents descriptive statistics for the sample. 2. Factorial ANOVA. Perform a factorial ANOVA using the \"Activity 5a.sav\" data set. a. Is there a main effect of gender? If so, explain the effect. Use post hoc tests when necessary (or explain why they are not required in this specific case). b. Is there a main effect of classroom size? If so, explain the effect. Use post hoc tests when necessary (or explain why they are not required in this specific case). c. Is there an interaction between your two variables? If so, using post hoc tests, describe these differences. d. Is there support for the researcher's hypothesis that girls would do better than boys in classrooms with fewer students? Explain your answer. e. Write up the results in APA style and interpret them. Be sure that you discuss both main effects and the presence/absence of an interaction between the two