Capella University Data Analysis and Application: Systolic Blood Pressure

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Multiple Regression Report
This assignment will help you understand proper reporting and interpretation of multiple regression. You will use the IBM SPSS Linear Regression procedure to accurately compute a multiple regression with the Regression Data file given in the resources. Use the DAA Template given in the resources to write up your assignment. 

Step 1
Write Section 1 of the DAA. Provide a context of the Regression Dataset. Specifically, imagine that you are a health researcher studying how well a measure of anxiety ( X1) and weight ( X2) predict systolic blood pressure ( Y) . In Section 1 of the DAA, articulate your predictor variables, the outcome variable, and the scales of measurement for each variable. Specify the sample size of the dataset.

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Multiple Regression Report This assignment will help you understand proper reporting and interpretation of multiple regression. You will use the IBM SPSS Linear Regression procedure to accurately compute a multiple regression with the Regression Data file given in the resources. Use the DAA Template given in the resources to write up your assignment. Step 1 Write Section 1 of the DAA. Provide a context of the Regression Dataset. Specifically, imagine that you are a health researcher studying how well a measure of anxiety ( X1) and weight ( X2) predict systolic blood pressure ( Y) . In Section 1 of the DAA, articulate your predictor variables, the outcome variable, and the scales of measurement for each variable. Specify the sample size of the dataset. Step 2 Write Section 2 of the DAA. Test the four assumptions of multiple regression. Begin with SPSS output of the three histograms on X1, X 2, and Y and provide visual interpretations of normality. Next, paste the SPSS output of the scatterplot matrix and interpret it in terms of linearity and bivariate outliers. Next, paste SPSS output of the zero-order correlations (Pearson r) and interpret it to check the multicollinearity assumption. Note: To test this assumption in SPSS, use Analyze… Correlate… Bivariate Correlations to generate a two-tailed test; do not use the default one-tailed test output from the Linear Regression procedure. Finally, paste the SPSS plot of standardized residuals (ZPRED = x-axis; ZRESID = y-axis) and interpret it to check the homoscedasticity assumption. Step 3 Write Section 3 of the DAA. Specify a research question for the overall regression model. Articulate a null hypothesis and alternative hypothesis for the overall regression model. Specify a research question for each predictor. Articulate the null hypothesis and alternative hypothesis for each predictor. Specify the alpha level. Step 4 Write Section 4 of the DAA. Begin with a brief statement reviewing assumptions. Next, paste the SPSS output for the Model Summary. Report R and R2; interpret R2 effect size. Next, paste the SPSS ANOVA output. Report the F test for R and interpret it against the null hypothesis. Next, paste the SPSS Coefficients output. For each predictor, report the b coefficient, the t test results, including interpretation against the null hypothesis, the semipartial squared • • • • • • • correlation effect size, and the interpretation of effect size. In your Interpretation section, following Table 11.1 on page 460 of your Applied Statistics text, generate a table of results for the Regression Dataset that summarizes: The means and standard deviations of each variable in the regression equation. The zero-order (Pearson r) correlations among variables. The y-intercept. The b coefficients of each predictor with notation of calculated p-values for rejecting the null hypothesis. The β coefficients of each predictor. The squared semipartial correlations of each predictor. The values of R, R2, and adjusted R2 with notation of p-values for rejecting the null hypothesis. Step 5 Write Section 5 of the DAA. Discuss your conclusions of the multiple regression as it relates to your stated research questions for the overall regression model and the individual predictors. Conclude with an analysis of the strengths and limitations of multiple regression. DATA ANALYSIS AND APPLICATION Data Analysis and Application Cornell Jones Capella University 1 DATA ANALYSIS AND APPLICATION 2 [Introduction.] Use this file for all assignments that require the DAA Template. Although the statistical tests will change from week to week, the basic organization and structure of the DAA remains the same. According to the sixth edition of Publication Manual of the American Psychological Association, the introduction of a manuscript is clearly identified by its position within it, and therefore does not have a heading to label it as the introduction. Remove this text and provide a brief introduction. Data File Description [one paragraph] 1) Describe the context of the data set. Cite a previous description if the same data set is used from a previous assignment. To increase the formal tone of the DAA, avoid first-person perspective “I.” For example, do not write, “I ran a scatter plot shown in Figure 1.” Instead, write, “Figure 1 shows…” All paragraphs are indented. Your paragraphs will not be numbered as these are in the template. 2) Specify the variables used in this DAA and the scale of measurement of each variable. 3) Specify sample size (N). Testing Assumptions [multiple paragraphs] 1) Articulate the assumptions of the statistical test. 2) Paste SPSS output that tests those assumptions and interpret them. Properly embed SPSS output where appropriate. Do not string all output together at the beginning of the section. In other words, interpretations of figures and tables should be near (i.e., immediately above or below) where the output appears. Format figures and tables per APA (6th edition) style and formatting rules. Refer to the following examples on the next page. DATA ANALYSIS AND APPLICATION 3 Figure 1. Scatter plot of IQ scores and ADDSC scores taken from a Howell (2011) data set. Figure 1 above shows the negative linear relationship between… Table 1 below shows the intercorrelations, means, and standard deviations of… Table 1 Intercorrelations, Means, and Standard Deviations for Scores on IQ, ADDSC, and GPA ______________________________________________________________________________ Measure 1 2 3 M SD ______________________________________________________________________________ 1. IQ -- 2. ADDSC -.63** -- 3. GPA .50** -.62** -- 100.26 12.99 52.60 12.42 2.46 .86 ______________________________________________________________________________ Note. Intercorrelations taken from a Howell (2011) data set (N = 88). **p < .01. DATA ANALYSIS AND APPLICATION 4 3) Summarize whether or not the assumptions are met. If assumptions are not met, discuss how to ameliorate violations of the assumptions. Research Question, Hypotheses, and Alpha Level [one paragraph] 1) Articulate a research question (or questions) relevant to the statistical test. 2) Articulate the null hypothesis and alternative hypothesis for the research question(s). 3) Specify the alpha level. Interpretation [multiple paragraphs] 1) Paste SPSS output for an inferential statistic and report it. Properly embed SPSS output where appropriate. Do not string all output together at the beginning of the section. In other words, interpretations of figures and tables should be near (i.e., immediately above or below) where the output appears. Format figures and tables per APA formatting rules. 2) Report the test statistics. Refer to Warner (2013) “Results” examples at the end of the appropriate chapter for guidance. 3) Interpret statistical results against the null hypothesis. Conclusion [two paragraphs] 1) Provide a brief summary (i.e., one paragraph) of the DAA conclusions. 2) Analyze strengths and limitations of the statistical test. DATA ANALYSIS AND APPLICATION 5 References Howell, D. C. (2011). Fundamental statistics for the behavioral sciences. (7th ed.). Belmont, CA: Wadsworth. 1) Provide references if you include in-text citations. Do not cite Capella course materials (e.g., instructor notes, handouts, class announcements, and so on). Only cite primary and secondary sources (e.g., textbooks and empirical journal articles). Be sure that your reference page remains on a separate page. Anxiety Weight 7 10 35 19 17 11 18 36 19 22 28 25 4 25 18 7 16 25 28 10 34 22 17 16 9 90 130 30 151 170 190 210 91 90 95 130 150 110 150 110 150 230 315 250 210 271 250 230 185 201 SBP 137 158 163 133 106 128 168 145 149 143 145 123 145 143 113 119 139 173 176 178 174 176 156 144 154
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DATA ANALYSIS AND APPLICATION

Data Analysis and Application
Cornell Jones
Capella University

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DATA ANALYSIS AND APPLICATION

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Systolic Blood Pressure
Systolic blood pressure is a measurement of a person’s blood pressure. A threshold value of
120mm of Hg is considered as normal systolic blood pressure. If the blood pressure reading is
too high, then hypertension is present. If the reading is too low, then there may be insufficient
blood flow to the critical organs such as the brain. The purpose of the paper is to predict the
systolic blood pressure of the individual from his/her anxiety and weight.
Data File Description
In order to predict the systolic blood pressure, individual’s weight, anxiety level and
measurement of systolic blood pressure were recorded. A random sample of 25 individuals is
considered for the study. All the variables are quantitative and measured on a ratio/interval scale.
The dependent variable is the individual’s systolic blood pressure. The independent variable used
in the study is the individual’s weight and level of anxi...


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