Homework Answers
In Model A Explanatory variable Train is not significantly effect on dependent variable.
because the p value is greater that significance level. hence we accept H0 i.e.β0 = 0
means that the Variable train is Not significant.
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To examine the differences between salaries of male and female middle managers of a large bank,...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered Salary the monthly salary (excluding fringe benefits and bonuses) Educ the number of years of education Exper the number of months of experience Train the number of weeks of training Gender- the gender of an individual; 1 for males, and O for females Excel partial outputs corresponding to these...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables consider...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered: Salary = the monthly salary (excluding fringe benefits and bonuses), Educ = the number of years of education, Exper = the number of months of experience, Train = the number of weeks of training, Gender = the gender of an individual; 1 for males, and 0 for females. Excel...
An over-the-counter drug manufacturer wants to examine the effectiveness of a new drug in curing an illness most commonly found in older patients. Thirteen patients are given the new drug and 13 patie...
An over-the-counter drug manufacturer wants to examine the effectiveness of a new drug in curing an illness most commonly found in older patients. Thirteen patients are given the new drug and 13 patients are given the old drug. To avoid bias in the experiment, they are not told which drug is given to them. To check how the effectiveness depends on the age of patients, the following data have been collected. To examine the differences between salaries of male and...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables cons...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered Salary- the monthly salary (excluding fringe benefits and bonuses), Educ the number of years of education, Exper the number of months of experience, Train the number of weeks of training, Gender- the gender of an individual; 1 for males, and O for females. Excel partial outputs corresponding to these...
An expert witness statistician was analyzing data from a workers compensation discrimination lawsuit filed by female...
An expert witness statistician was analyzing data from a workers compensation discrimination lawsuit filed by female workers at a bank. The data provided to the expert contain the following information: SALARY in dollars), EDUCAT (number of years of schooling), EXPER (# of months of work experience prior to joining the bank), MONTHS (# of months since joining the bank), MALES (an indicator for a worker's gender: 0 for a female, 1 for a male). As part of the investigation, the...
QUESTION 27 Q27. A manager at a local bank analyzed the relationship between monthly salary (y,...
QUESTION 27 Q27. A manager at a local bank analyzed the relationship between monthly salary (y, in $) and length of service (x, measured in months) for 30 employees. She estimates the model: Salary = Bo + B1 Service + ε. The following ANOVA table below shows a portion of the regression results. df SS M S F Regression 555,420 555,420 7.64 Residual 27 1,962,873 72,699 Total 28 2 ,518,293 Coefficients Standard Error t-stat p-value Intercept 784.92 322.25 2.44 0.02...
ek-tin Based on the following regression output, what proportion the total variation in Y is explained...
ek-tin
Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 0.917214 o b.9.385572...
19. A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the...
19. A sociologist examines the relationship between the poverty rate and several socioeconomic factors. For the 50 states and the District of Columbia (n = 51), he collects data on the poverty rate (y, in %), the percent of the population with at least a high school education (x1), median income (x2, in $1000s), and the mortality rate per 1,000 residents (x3). He estimates the following model as y = β0 + β1Education + β2Income + β3Mortality + ε. The...
The effect of mean monthly daily temperature and cost per kilowatthour x, on the mean daily...
The effect of mean monthly daily temperature and cost per kilowatthour x, on the mean daily household consumption of electricity (in kilowatt-hours, kWh) was the subject of a short-term study. The investigators expected the demand for electricity to rise in cold weather (due to heating), fall when the weather was moderate, and rise again when the temperature rose and there was need for air-conditioning. They expected demand to decrease as the cost per kilowatt-hour increased, reflecting greater attention to conservation....
B. The table below lists the sales, y (in millions of dollars) and the number of...
B. The table below lists the sales, y (in millions of dollars) and the number of employees, x (in thousands) for a random sample of 20 Fortune 500 companies. The regression results based on the model are given below. Some of the numbers in the regression tables have been taken out. SUMMARY OUTPUT Regression Statistics Multiple R (1) R Square (2) Adjusted R Square 0.837364 Standard Error (3) Observations (4) ANOVA df SS MS F Significance F Regression (5) (7)...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered Salary the monthly salary (excluding fringe benefits and bonuses) Educ the number of years of education Exper the number of months of experience Train the number of weeks of training Gender- the gender of an individual; 1 for males, and O for females Excel partial outputs corresponding to these...
To examine the differences between salaries of male and female middle managers of a large bank, 90 individuals were randomly selected, and two models were created with the following variables considered Salary- the monthly salary (excluding fringe benefits and bonuses), Educ the number of years of education, Exper the number of months of experience, Train the number of weeks of training, Gender- the gender of an individual; 1 for males, and O for females. Excel partial outputs corresponding to these...
An expert witness statistician was analyzing data from a workers compensation discrimination lawsuit filed by female workers at a bank. The data provided to the expert contain the following information: SALARY in dollars), EDUCAT (number of years of schooling), EXPER (# of months of work experience prior to joining the bank), MONTHS (# of months since joining the bank), MALES (an indicator for a worker's gender: 0 for a female, 1 for a male). As part of the investigation, the...
QUESTION 27 Q27. A manager at a local bank analyzed the relationship between monthly salary (y, in $) and length of service (x, measured in months) for 30 employees. She estimates the model: Salary = Bo + B1 Service + ε. The following ANOVA table below shows a portion of the regression results. df SS M S F Regression 555,420 555,420 7.64 Residual 27 1,962,873 72,699 Total 28 2 ,518,293 Coefficients Standard Error t-stat p-value Intercept 784.92 322.25 2.44 0.02...
ek-tin
Based on the following regression output, what proportion the total variation in Y is explained by X? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA di SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 Residual 8 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 0.917214 o b.9.385572...
The effect of mean monthly daily temperature and cost per kilowatthour x, on the mean daily household consumption of electricity (in kilowatt-hours, kWh) was the subject of a short-term study. The investigators expected the demand for electricity to rise in cold weather (due to heating), fall when the weather was moderate, and rise again when the temperature rose and there was need for air-conditioning. They expected demand to decrease as the cost per kilowatt-hour increased, reflecting greater attention to conservation....
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