The yield of cotton appears to be sensitive to rainfall. An agricultural experiment station collected the following records about June rainfall and yield of cotton. Is cotton yield impacted by rainfall? June rainfall (cm) 3 6 7 9 11 15 17 19 Yield (lb/acre) 1120 1750 1940 2130 2380 2650 2990 3130 b. Perform a regression analysis. Define your hypothesis, state your conclusions, and show all work.
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?2300The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 Based on the multiple regression output, if GPA and civil service ratings are held fixed, how much is the expected increase in the starting salary (pesos) for every one year increase in the years of experience?
- The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 In the ANOVA F test output, what is the computed F and the conclusion of the test regarding the overall significance of the model?Consider the SPSS regression output below. The dependent variable (Y) is the level of happiness felt by individuals. The dependent variable was measured in the following manner: 1= very unhappy, 2= somewhat unhappy, 3=neither unhappy nor happy, 4= somewhat happy, 5= very happy. The following four factors are the independent variables: highest year of school completed, respondent’s age, number of children of the respondent, and total family income. The researcher acquired data from 1,457 randomly selected Americans and ran a multiple regression. The regression results are presented below: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .215a .046 .043 .72476 a. Predictors: (Constant), TOTAL FAMILY INCOME, AGE OF RESPONDENT, NUMBER OF CHILDREN, SUBJECTIVE CLASS IDENTIFICATION, HIGHEST YEAR OF SCHOOL COMPLETED Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig.…A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
- A researcher wants to predict the effect of the number of times a person eats every day and the number of times they exercise on BMI. What statistical test would work best? A. Pearson's R B. Spearman Rho C. Linear regression D. Multiple regressionA professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
- The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Copy-paste the data and run the analysis using MS Excel. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 What is the computed R square of the resulting multiple linear regression and its interpretation?The regional transit authority for a major metropolitan area wants to determine whetherthere is a relationship between the age of a bus and the annual maintenance cost. A sampleof ten buses resulted in the following data: a. Develop a scatter chart for these data. What does the scatter chart indicate about therelationship between age of a bus and the annual maintenance cost?b. Use the data to develop an estimated regression equation that could be used to predictthe annual maintenance cost given the age of the bus. What is the estimated regressionmodel?c. Test whether each of the regression parameters b0 and b1 is equal to zero at a 0.05level of significance. What are the correct interpretations of the estimated regressionparameters? Are these interpretations reasonable?d. How much of the variation in the sample values of annual maintenance cost does themodel you estimated in part b explain?e. What do you predict the annual maintenance cost to be for a 3.5-year-old bus?Is the price of a smartphone affected by its display size, camera resolution, or internal storage capacity? Perform a regression analysis on the SmartphoneDCS dataset using MegaStat and answer the following questions. The level of significance is .05. When you copy and paste output from MegaStat to answer a question, remember to choose to "Keep Formatting" to paste the text. a. Do the data conform to Evans' Rule? What about Doane's Rule? Show the calculations to explain the reason for your answers.b. What is the critical value for the F test?c. Perform the regression and state the regression equation.d. Copy and paste the ANOVA table from your analysis. Is the overall fit of the model significant or not? Use your answer to part (b) to explain your decision.e. What is the coefficient of determination and the adjusted coefficient of determination for your analysis? What do these two coefficients tell you about the variation of price in your model?
