Additional information was obtained from EXCEL. Conduct a test of hypothesis to determine if any of the regression coefficients do not equal 0. Use the 0.05 significance level. The regression a. equation is: Salary = 19.2 + 3.10 Years +0.269 Perform -0.704 Absent %3D t Stat P-value 1.580 0.143 4.385 0.001 Coefficients Standard Error Intercept Years 19.186 12.146 3.096 0.706

on the first statistics exam, the coefficient of determination between the hours studied and the grade earned was 80%. the standard error of the estimate was 15. there were 20 students in the class. develop ANOVA table for the regression analysis of hours studied as a predictor of the grade earned on the first statistics exam.

Need help writing a null hypothesis for the bivariate relationship shown in the SPSS output.

What percentage of the variation in  can be explained by the corresponding variations in  and  taken together?

Many high school students take either the SAT or the ACT. However, some students take both. Data were collected from 100 students who took both college entrance exams. The average SAT score was 920 with a standard deviation of 170. The average ACT score was 20 with a standard deviation of 5. The correlation coefficient r between these two variables equals 0.82. To predict the SAT score from a student’s ACT score, what is the equation of the least-squares regression line? Please show your work.

Based on the scatter plot above, describe the relationship between the amount of cost damage and the distance from nearest fire station to the residential.    Determine the regression line for the above regression output.    Interpret the slope coefficient of distance to the nearest station affecting the amount of fire cost damage.    Compute the correlation coefficient and interpret its meaning.    Does the distance to the nearest fire station has significant influence on the cost damage amount? Conduct a test at 1% significance level. ]   Predict the fire cost damage generated if the distance from nearest fire station is 2.5 kilometers. Is this estimate reliable? Explain. []

Listed below are the overhead widths​ (cm) of seals measured from photographs and weights​ (kg) of the seals. Find the regression​ equation, letting the overhead width be the predictor​ (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is1.8​cm, using the regression equation. Can the prediction be​ correct? If​ not, what is​ wrong? Use a significance level of 0.05. Overhead_Width_(cm)    Weight_(kg)7.2    1287.4    1679.8    2619.5    2218.7    2118.3    201 The regression equation is y=enter your response here+enter your response herex. ​(Round the​ y-intercept to the nearest integer as needed. Round the slope to one decimal place as​ needed.) Part 2 The best predicted weight for an overhead width of 1.8 ​cm, based on the regression​ equation, is enter your response here kg. ​(Round to one decimal place as​ needed.) Part 3 Can the prediction be​ correct? If​ not, what is​ wrong?     A. The prediction cannot be correct…

A researcher plans to study the causal effect of police on crime using data from a random sample of U.K. counties. He plans to regress the county’s crime rate on the (per capita) size of the county’s police force. Explain why this regression is likely to suffer from omitted variable bias. Which variable would you add to the regression to controlfor important omitted variable? Determine whether the regression will likely over or underestimate the effect of police on the crime rate?

Anagha is interested in buying a new Model X car and wants to gather information about how the selling price of the car is related to the year of the model. She randomly selects 24 used Model X cars for sale. For each used car, she records the car’s selling price (in dollars) and age (in years). She computes a 96 percent confidence interval to estimate the slope of the regression line relating the age of a used Model X car to its selling price. The resulting confidence interval is given by (−5,556,−3,157). Assume that the conditions for inference on the slope of the regression equation are met. Which of the following is the correct interpretation of the confidence interval?     We are 96 percent confident that a Model X car will have a predicted decrease in selling price of between $3,157 and $5,556. A Ninety-six percent of the time, a one-year increase in the age of a Model X car will result in a predicted decrease in selling price of between $3,157 and $5,556. B…

The Average final score was 78, the average midterm score was 80. The standard deviation for the average final midterm score was 4.5 and the standard deviation for the average midterm score was 5.5. The correlation coefficient is 0.76 Find the least squares regression line. Supposed that wanted to find to predict the final exam score based the midterm score