$FL2@(#) IBM SPSS STATISTICS DATA FILE MS Windows 20.0.0 #########################Y@27 Sep 1215:11:42 ###########################CASE ########################XAGE ####IV Age ########################ZEXER ####IV Exercise ########################YENDU ###DV Endurance############################################################## ############ ##############################################################+###CASE=case XAGE=xage ZEXER=zexer YENDU=yendu###########################################I###case:$@Role('0' )/xage:$@Role('0' )/zexer:$@Role('0' )/yendu:$@Role('0' )############ ###windows1252#######fmgfjjmmthyuhyijivh}fmjmmikrdk fyi|gof|knjkkh~guixgzjxjyhk~##### c@#####d@ktj#####d@######e@kl#####e@#####`g@myxj| #####g@#####g@jm#####i@#####@j@fyiz#####j@#####@k@lm#####l@#####` m@gkx######n@#####@n@l~g#####`n@#####n@im{phqgphxj~dhzi mmmskinlq mkvjgezmkkl#####@d@#####e@imr#####h@#####`i@gj} #####@l@#####@m@k}l}#####m@#####m@j|m##### n@#####n@kllzl}jmkimtjzh~hsmx#####d@#####@e@mlw##### f@#####f@jyif##### h@#####j@dgkd#####n@######o@xqqopqqnqpvpopnquq{ n#####`e@no#####@f@#####g@oqp######h@######i@o| o#####j@#####l@orhnv#####m@}nq|nowpnqvqon n|p po{noooqn{#####f@nwny######g@#####h@qyqx#####h@#####@i@p oy######j@#####`k@qp#####k@#####l@env{q~oq}pqqo}nqnznl on#nkpzptporqtpwpkqqoqornpu#####@c@oo#####`c@#####c@ nzo######d@#####d@nupy#####e@#####f@otnt#####g@#####i@p| o######k@##### m@nxov#####n@##### o@p|lw#####@o@svL}sr xr~r######c@rr#####e@#####h@ux#####i@##### k@urz#####k@#####k@unrs######l@|rsr| ttsrrsrtzrrt{#####c@snrs#####c@#####@h@y~sm##### i@##### j@vyr}#####`j@#####j@wt#####k@##### l@xos######m@rus| vtwr}wtrroru ru ~ svvv#####c@##### d@tv#####`d@##### e@ss|#####`f@#####f@tv##### g@#####@g@s| z#####`l@#####l@s#########m@ Homework Assignment #3 & #4 EDRE Regression Part I Hypothetical Data file to use: HW_Assignment#3 (I modified the data a little bit from what I used in the lecture!). For all questions, please use linear regression. Use gender, Cites, Pubs, and Time as your independent variables, and use salary as your dependent variable. Please note: I changed the data, so your values will NOT be the same as what I have used in the lecture notes. All methods are in my lecture notes.... 1. Run the multiple regression analysis. a. Report the slope values (unstandardized) for each of the predictors. b. Which of the predictors was significant? c. Please provide a one sentence interpretation for each of the slopes. 2. Let's examine if there are any outliers in this dataset? a. Convert each variable to z-scores and determine if there are any univariate outliers. If you find one, please report the case number and explain why this case (i.e., participant) is a univariate outlier. b. Obtain the Mahalanobis distance for each of the independent variables. Which case number if any revealed a significant multivariate outlier. Be sure to explain why you determined that the Mahalanobis distance value was a significant outlier. 3. Re-run the multiple regression after deleting those cases that are either univariate or multivariate outliers. a. Report the slope values, and indicate which of the slopes were significantly different from zero. b. Were there any differences between the findings found in 1b and 3a? Which of the slopes changed from being significant to non-significant (or vice versa)? c. What would you do if you were a researcher interested in testing a theory suggesting that number of publications was causally related to increases in faculty salaries?? Would you report the regression results from the analysis that included all of the data or would you delete these outliers? What else could you possibly do?? 4. Please find one research article published in an educational research journal (e.g., American Educational Research Association Journal, Journal of Educational Psychology, etc). It is likely that there are many analyses in the article that you found. Just pick one multiple regression analysis that is reported in the journal for the questions below. a. What is the null and alternative hypotheses. (note: it is unlikely that the authors will state the null/alternative....but you can easily state these two hypotheses). b. Report the regression findings with respect to the relations between the independent variables and the dependent variable. Note that the article may only report R2 or perhaps only the regression coefficients. Just pull from the article the relevant parameter estimates used in the regression analysis which indicate relations between the DV and the IV's. c. Using plain English, please summarize in a couple sentences what the regression analysis indicated. Pretend you are explaining the findings to your grandmother - just indicate what was found and do not use any technical \"regression jargon\". Part II Hypothetical Data file to use: Another_file_Lecture#5_fromChapter7.sav (I did not modify the data from what I used in the lecture!). For all questions, please use linear regression. Use age and exercise and an interaction variable as the IV's and endurance as the DV. Please note: I have not changed the data, so your values will be the same as what I have used in the lecture notes. All methods are in my lecture notes.... 1. Run the multiple regression analysis. (important: you will need to create an interaction variable and include it as a 3rd predictor in this regression analysis). a. Report the slope values (unstandardized) for each of the predictors. b. State the null and alternative hypotheses for each of the predictors (including the interaction term). c. Which of the predictors was significant? d. Interpret the interaction term using the steps in the lecture notes. First, convert age and exercise variables into categorical variables with 3 ordinal levels. Next, use the scatterplot figure to fit the line of one IV at different levels of the other IV. Report that scatterplot with the 3 lines shown. (Note: the how-to is all included in the lecture slides) e. Interpret the interaction term based on the figure that you created with the scatterplot. 2. Suppose you are evaluating a reading intervention for a school district. The study design includes 2 independent variables. The first independent variable is intervention group with two levels: reading intervention treatment A coded a 0 and reading intervention treatment B coded a 1). The second independent variable is a quantitative measure of fidelity of implementation of the intervention, with a 0 coded for \"low fidelity\" and a 1 coded for \"high fidelity\". For the following questions, pretend that you are describing regression results to a district reading content area director who has no formal training in statistics. Assume the dependent variable is percentage correct on a word recognition test, and that the main effects and interaction terms are significant at p < .001. a. In no more than 2 sentences, please describe what the main effect for intervention group means, assuming the slope is 3.5. b. In no more than 2 sentences, please describe what the main effect for fidelity independent variable, assuming that the slope is .8. c. 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