In running a logistic regression, a statistician decided to include decade of life (20s, 30s, 40s, 50s, 60s) as a categorical variable in the systematic component because they didn't believe the relationship between the log-odds and age was linear. Using dummy variables to create the systematic component, how many dummy variables would be needed to represented age?

10)   A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)

A correlation of 0.95 for two variables X and Y implies that if X increases, there is a 95% chance that Y will also increase. Is this statement true or false?

Below is some of the regression output from a regression of the amount various customers paid for a new car (expressed in dollars) versus the age of the customer (expressed in years), the number of previous cars the customer had purchased from the dealership in the past, a dummy variable indicating the gender of the customer (=1 for a Man and = 0 for a woman), and an interactive term the multiplies the age of the customer with the gender dummy variable.  Regression Statistics           Multiple R 0.963           R Square             Adjusted R Square             Standard Error             Observations 20                         ANOVA               df SS MS F Significance F Regression   24686354.49 6171589 47.8 2.3289E-08   Residual     129243       Total   26625000…

A research study was conducted at a local college collecting data on the models (brands) of cars parked in the student parking lot.  This type of data collected would be considered/described as Qualitative Data or Quantitative Data?

How does linear regression differ from analysis of variance?

You work as a data scientist for a real estate company in a seaside resort town. Your boss has asked you to discover if it's possible to predict how much a home's distance from the water affects its selling price. You are going to collect a random sample of 7 recently sold homes in your town. You will note the distance each home is from the water (denoted by x, in km) and each home's selling price (denoted by y, in hundreds of thousands of dollars). You will also note the product x.y of the distance from the water and selling price for each home. (These products are written in the row labeled "xy"). (a) Click on "Take Sample" to see the results for your random sample. Distance from the water, .x (in km) Take Sample Selling price, y (in hundreds of thousands of dollars) xy Send data to calculator Based on the data from your sample, enter the indicated values in the column on the left below. Round decimal values to three decimal places. When you are done, select "Compute". (In the table…

Why is the concept of variability important?

What is the Fratio for these data?

Would the regression in Equation be useful for predicting test scoresin a school district in Massachusetts? Why or why not?