longley is a built-in R data.frame which is sometimes used in economics to study regression. We are interested in some descriptivestatistics related to the Employed column of the longley data.frame. We can access this data directly by using the assignmentx <- longley$Employed(In R, use ? Longley for info on this data)The values of x if assigned as above are:[1] 60.323, 61.122, 60.171, 61.187, 63.221, 63.639, 64.989, 63.761[9] 66.019, 67.857, 68.169, 66.513, 68.655, 69.564, 69.331, 70.551You should get these values from the R assignment above rather than manually entering the data.e. Calculate the sample mean of x.f. Calculate the sample variance of x.g. Calculate the sample standard deviation of x.h. What proportion of the x values are less than 1 sample standard deviation from the sample mean?i. Calculate the sample median of x.j. What is the 9th element of x?k. How many of the elements of x are smaller than the sample mean of x?

Solution -Given that , The values of x are as follows x: 60.323, 61.122, 60.171, 61.187, 63.221,…

Answered: longley is a built-in R data.frame…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

See similar textbooks

Similar questions

The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Answer these question
Please explain step by step how you solved for each problem, and where the numbers came from.
Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)
The table shows the national expenditures for health care in billions, in a country for the selected years from 1990 to 2020. Given the projection cost for the year 2002, identify the type of regression point. Year Exprenditures ($billions) 1991 1020 1994 1356 1998 1984 2004 2984 2009 3374 2016 4765 2020 5937 Interpolation Extrapolation Neither Both
The following data gives the number of employees at the bookstore and the number of minutes students wait in line to buy books at the beginning of the term. The independent variable is the number of employees and the dependent variable is the number of minutes. What is the y intercept? SSxx = 56.857; SS=2095.714; SSxy=-322.571 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square XA356899 0.96 0.93 0.91 y 67 54 47 33 31 25 12
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 762 51 621 46 515 45 508 42 491 39 480 36 (a) x = 502 feet (c) x = 315 feet Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) (b) x = 645 feet (d) x = 731 feet
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 130 120 90 190 (a) x=160 calories (b) x=100 calories Sodium, y 430 480 320 360 290 550 (c) x=140 calories (d) x=50 calories Find the regression equation. y=nothingx+(nothing) (Round to three decimal places as needed.) Choose the correct graph below. A. 02000560CaloriesSodium (mg) A scatterplot has a horizontal axis labeled "Calories" from 0 to 200 in increments of 20 and a vertical axis labeled "Sodium (in milligrams)" from 0 to 560 in increments of…
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 130 130 350 370 150 (a) x 160 calories (b)x= 100 calories Sodlum, y (c) x 140 calories (d) x=200 calories Find the regression equation. (Round to three decimal places as needed.) Choose the correct graph below. OA 560 Q Q 200 G Calories (a) Predict the value of y for x = 160. Choose the correct answer below. OA. 393.094 OB. 440.954 OC. 536.674 OD. not meaningful (b) Predict the value of y for x= 100. Choose the correct answer below. OA 297.374 OB. 536.674 OC. 393.094 OD. not meaningful (c) Predict the value of y for x = 140. Choose the correct answer below. OA 297.374 OB.…
Based on the line of best fit for the data below, select which choice best predicts the y-value when the x-value is 10. -80 -75 -70 -65 -60 -55- -50+ -45- -40- -35 -30- -25 -20+ -15 -10 -5- 0 O O O O 96 80 91 85 8 10 11 12
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x 150 180 120 130 90 190 P (a)x= 170 calories (c) x 140 calories (b)x= 100 calories (d) x = 210 calories Sodium, y 430 480 350 370 290 530 REED Find the regression equation. ŷ=x+0) (Round to three decimal places as needed.) 4

SEE MORE QUESTIONS

Recommended textbooks for you

A First Course in Probability (10th Edition)

Probability

ISBN:

9780134753119

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability

Probability

ISBN:

9780321794772

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability (10th Edition)

Probability

ISBN:

9780134753119

Author:

Sheldon Ross

Publisher:

PEARSON

A First Course in Probability

Probability

ISBN:

9780321794772

Author:

Sheldon Ross

Publisher:

PEARSON

SEE MORE TEXTBOOKS