In a study, data collected for 40 observations were used to model the dependent varlable independent variables under consideration, x1, x2, ... , Xg. Consider a stepwise regression run on the 1 What is the form of the model fit in step 1? How many models are fit? How is the "best" independer

Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relating fertility to years of education is: kids; = Bo + B1educ; + uż. 1. What are the parameters in the model? 2. What kinds of factors are contained in u? Are these likely to be cor- related with level of education? 3. Will a simple regression analysis uncover the ceteris paribus effect of education on fertility? Explain.

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If a scatterplot is created in excel, and a line of regression is fit along with a derived functional form, what does it mean to describe and interpret them? What conclusions would be made about relationships between two recorded variables?

The following table shows the starting salary and profile of a sample of 10 2 p 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.What is the computed R square of the resulting multiple linear regression and its interpretation? * Civil Years of Starting salary GPA service experience ratings 79.5 15000 80.1 15000 81.2 78.0 15500 81.3 79.0 16000 82.4 80.0 16200 83.4 85.0 17500 87.9 89.9 89.1 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 84.1 89.0 89.2 R squared = 0.8053; This means that 80.53% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of…

Using data from 50 clerical workers, a researcher estimates Wage = B0 + B1Education + B2Experience + B3Age + E, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Standard Error Coefficients t Stat p-Value Intercept 0.0603 0.0001 7.90 4.09 1.93 Education 2.44 0.34 4.24 Experience Age 0.54 0.14 3.16 0.0028 -0.02 0.08 -0.14 0.8920 What is the sample regression equation (round to 2 decimal places)? Education + Experience + Age What is the hourly wage for a 30-year-old worker with 4 years of higher education and 3 years of experience (round to 2 decimal places)? Are any independent variables insignificant at a 95% level of significance? (Y/N)

A study was conducted on 64 female college athletes. The researcher collected data on a number of variables including percent body​ fat, total body​ weight, height, and age of athlete. The researcher wondered if​ % body fat​ (%BF), height​ (HGT), and/or age are significant predictors of total body weight. All conditions have been checked and are met and no transformations were needed. The technology output from the multiple regression analysis is given below. Interpret the coefficient of​ % body fat

The​ least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a​ bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962.  In a particular​ region, 26.5 percent of adults 25 years and older have at least a​ bachelor's degree. The median income in this region is ​$29,889. Is this income higher or lower than what you would​ expect? Why?

The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Month Number of Accidents Jan 25 Feb 40 Mar 60 Apr 90 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): ŷ-0-0x Using least-squares regression, the forecast for the number of accidents that will occur in the month of May = accidents (enter your response as a whole number).