Use the given data set to complete parts (a) through (c) below. Use of = 0.05.

 x       10        8         13         9         11        14          6        4         12         7        5

 y      7.45    6.77    12.74     7.11     7.81     8.83     6.08     5.39     8.14     6.42    5.74

 

a. Construct a scatterplot. Choose the correct graph below.

(1 point) In the study of red/green color blindness, 750 men and 2750 women are randomly selected and tested. Among the men, 64 have red/green color blindness. Among the women, 6 have red/green color blindness. Test the claim that men have a higher rate of red/green color blindness.

(a) State the null hypothesis:

(b) State the alternative hypothesis:

(c) The test statistic is

(d) Is there sufficient evidence to support the claim that men have a higher rate of red/green color blindness than women? Use a 1% significance level.

A. Yes

B. No

(e) Construct the 99% confidence interval for the difference between the color blindness rates of men and women.

(1 point) 1. In a study of red/green color blindness, 850 men and 2450 women are randomly selected and tested. Among the men, 72 have red/green color blindness. Among the women, 5 have red/green color blindness. Test the claim that men have a higher rate of red/green color blindness.

The test statistic is

The p-value is

 Is there sufficient evidence to support the claim that men have a higher rate of red/green color blindness than women using the 0.01% significance level?

A. Yes

B. No

2. Construct the 99% confidence interval for the difference between the color blindness rates of men and women.

Which of the following is the correct interpretation for your answer in part 2?

A. We can be 99% confident that the difference between the rates of red/green color blindness men and women lies in the interval

B. There is a 99% chance that the difference between the rates of red/green color blindness men and women lies in the interval

C. We can be 99% confident that the difference between the rates of red/green color blindness men and women in the sample lies in the interval

D. None of the above.

Opeele Kyinkafa sells different used 2005 GM cars in excellent condition. The value or the retail price (Price) of a car is dependent on a variety of characteristics such as number of miles the car has been driven (Mileage), manufacturer of the car (Make) such as Buick, Cadillac, Chevrolet, Pontiac, SAAB, and Saturn. The car price is also influenced by the body type (Type) such as sedan, convertible, coupe, hatchback and wagon. It is also affected by number of cylinders (Cylinders) in the engine, the engine size (Liter), cruise control which is an indicator variable representing whether the car has cruise control (yes) or no otherwise and Sound indicator representing whether the car has upgraded speakers (yes) or no otherwise. All cars in this data set were less than one year old when priced and considered to be in excellent condition. Determine which major variables are dummies and are dynamic? Identify 3 potential unobserved heterogenous factors in this dataset. Display the full descriptive statistics of the data in R. Why do you think some variables are starred (*)? What is the median for “price”, standard deviation for “mileage”, skewness for “cylinder” and mean for “sound”? Test if “price” is normally distributed using histogram, kernel density plot and the shapiro wilk test. Create a red scatterplot matrix of price, mileage, cylinder, liter, make. From your graph, is the correlation between price & mileage positive or negative? What’s the pearson correlation coefficient between price & mileage and between “cylinder” & “liter” correct to 2 d.p Create a correlation matrix of the dataset by finding the apt R command for converting all string/dummy variables From the matrix, identify 2 potentially good predictors? Identify 3 pairs of variables that are mostly multicollinear. Which 2 pairs of variables are least correlated? Identify 3 pairs of variables most highly correlated with Cylinder Generate a simple regression plot of price on mileage with a re fitted line. Run the whole multiple regression model (label the equation as "regprice") & use it to answer the other questions. Specify the regression model for the whole data keeping the exact names of the variables. Write the estimated regression equation. In one sentence, which variables are significant and which are not? Justify Is the regression model justifiable? Explain Interpret the coefficient of Mileage, MakeCadillac, TypeSedan, Cylinder, & Cruiseyes. Compare the price of a car with 130,000 mileage, 6 cylinders, 3.8 liters, with cruise and sound, was manufactured by Pontiac with a convertible body type with that of the price of a car with four cylinders, 120,000 mileage, 3.8 liters, without cruise nor sound, was manufactured by Cadillac with a hatchback body type. Which factor(s) appears to be causing a comparative difference (if any)? Using only the VIF, which one of the pairs of variables selected to be multicollinear may be deleted? Justify?