EDUC 8 l 2 WRITE-UP: BIVARIATE REGRESSION TENIPLATE Instructions: For this graded assignment, you will complete the write-up below after completing the corresponding tutorial to this assignment. You will delete figures and tables where appropriate and then insert correct figures and tables. Also delete and then insert correct answers where there is RED text Scenario: The purpose of this study was to see if the number of nurses employed at a hospital could predict patient satisfaction. Researchers examined 20 hospitals similar in size and location. The amount of nurses working full-time for the hospitals were gathered from HR and patient satisfaction was averaged from surveys gathered over the past year. The patient satisfaction survey ranges from 1 to 10 with 1 being not satisfied and 10 being extremely satisfied. To begin, select the \"Data View\" tab, then cut and paste the data set below into SPSS (or you can type in the data manually). Do n_ot copy the header row when you paste into SPSS. Code Hospital Name pi Number of Nurses Bata Health 7.0 Patient Satisfaction LIILUJM \\'ION Med Win_ - Center 00 Ome - _a Health Center 7 1 7 4 _6S 5.4 Zenith Hos ital 198 6 0 9 0 7 3 6 3 91 1 Lake Shore Med Center 250 5 5.3 7.0 7.4 8.2 7.1 EDUC 8 l 2 FINDINGS Overview The purpose of this study was to see if the number of nurses employed could predict patient satisfaction. The independent variable was the number of nurses employed. The dependent variable was patient satisfaction as measured by the Patient Satisfaction Survey. A bivariate regression was used to test the hypothesis. The Findings section includes the research question, null hypothesis, data screening, descriptive statistics, assumption testing, and results. Research Question RQ: Is there a significant predictive relationship between the independent variable (number of nurses employed) and the dependent variable (patient satisfaction) for a group of similar hospitals? Null Hypothesis Ho: There is no signicant relationship between the independent variable (number of nurses employed) and the dependent variable (patient satisfaction) for a group of similar hospitals. Data Screening The researcher sorted the data and scanned for inconsistencies on each variable. No data errors or inconsistencies were identied. A scatter plot was used to detect bivariate outliers between the independent variable and the dependent variable. No bivariate outliers where identified. See Figure l for the scatter plots. EDUC 812 Figure 1 Simple Scatter Plot R2 Linear = 0.850 10 y=1.29+0.03*x Satisfaction . . 150 200 250 300 350 Nurses Descriptive Statistics Descriptive statistics were obtained on each of the variables. The sample consisted of 20 participants. The number of nurses at each hospital was obtained through HR. Patient satisfaction scores were obtained through averaging surveys obtained throughout the past year. Patient satisfaction scores could range from 1 (not satisfied at all) to 10 (extremely satisfied). Descriptive statistics can be found in Table 1.EDUC 8 l 2 Table 1 Descriptive Statistics N Minimum Maximum Mean Std. Deviation Nurses 20 157 301 209.50 35.289 Satisfaction 20 5 9 7.23 1.083 Valid N (listwise) 20 Assumption Testing Assumption of Linearity The multiple regression requires that the assumption of linearity be met. Linearity was examined using a scatter plot. The assumption of linearity was met. See Figure l for the bivariate scatter plot. Assumption of Bivariate Normal Distribution The bivariate regression requires that the assumption of bivariate normal distribution be met. The assumption of bivariate normal distribution was examined using a scatter plot. The assumption of bivariate normal distribution was met. See Figure 1 for scatter plot. EDUC 8 l 2 Results A bivariate regression was conducted to see if the number of nurses employed at a hospital could predict patient satisfaction. The independent variable was the number of nurses employed. The dependent variable was patient satisfaction scores as measured by the Patient Satisfaction Survey. The researcher rejected the null hypothesis at the 95% condence level where F(1, 18) : 102.18, p <.001. there was a statistical relationship between the independent variable of nurses and dependent satisfaction see table for regression model results. sum sguares df mean sguare f sig. residual .186 total a. variable: b. predictors: effect size extremely large where r : .922. furthermore r2 .850 indicating that approximately variance can be explained by variable. summary. educ summary adjusted std. error square estimate>