Path-HomeCtablearn.hawkeslearning.com/Portal/Lesson/lesson_certify- Exit Certify Lesson: 12.2 Linear RegressionQuestion 3 of 5, Step 1 of 6escaltBlackboard Learn!AnswerHow to enter your answer (opens in new window)1Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.9a=The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, bo + bx, forpredicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, inpractice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.Z← →@2WSXX#3edCC$4Lesson 12.2 Certify Mode Que xrf%Age36 51 63 66 70Bone Density 359 357 328 314 3105VtgOll6byhpb My Questions | bartlebyh7/18Correct&7nuj*8NOim(9Xk4O011Determine if the correlation b xalt4Р>:TAMARA BROOKSTables;ctrlKeypadKeyboard ShortcutsSubmit Answer{[4+Copy Data=1110?Dec 21Table}31:33backspace1<a^

Slope formula: slope=n∑XY-∑X∑Yn∑X2-∑X2

Answered: The table below gives the age and bone…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, Y=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in dollars 31 38 42 44 46 Number of Bids 3 4 6 7 9 Summation Table X Y XY X2 Y2 BID 1 31 3 93 961 9 BID 2 38 4 152 1444 16 BID 3 42 6 252 1764 36 BID 4 44 7 308 1936 49 BID 5 46 9 414 2116 81 SUM 201 29 1219 8221 191 Step 1: Find the estimated slope. Step 2: Find the estimated y-intercept. Step 3: Determine the value of the dependent variable Y at x=0. Step 4: Find the estimate value of y when x=42. Step 5: Substitute the values you found in steps 1 and 2 into the equation for the…
Which of the following statements is sensible? A 102.4% of the total variation in a football player's weight is accounted for, or explained by its linear regression with the time spent practicing football. B. The correlation coefficient between a car's length and its fuel efficiency is7 es per gallon. C. There is a very strong direct linear correlation (0.95) between amount of d od consumption and the brand of dog food. D. The correlation coefficient between the amounts of fertilizer used and quantity of beans harvested is 0.42. OD O A OB
A doctor has collected data on cholesterol, blood pressure, and weight. She also collected data on the eating habits of the subjects (eg. how many ounces of red meat, fish, dairy products, and chocolate consumed per week) She wants to investigate the relationship between the three measures of health and eating habits. Which statistical test can be best used for this study? a.Linear Regression b. Correlation Coefficient c. Frequency Distribution Table d. ANOVA
The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 124 143 158 160 196 Number of Bids 12 13 15 16 20 Table Step 2 of 6 : Find the estimated y-intercept. Round your answer to three decimal places.
Let x be the weight of a car (in hundreds of pounds), and let y be the miles per gallon (mpg). Suppose a car weighs 3800 pounds. What does the data forecast for the miles per gallon expected? x= 27 44 32 47 23 40 34 52 y= 30 19 24 13 29 17 21 14 State the correlation coefficient and state the regression lin equation.
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Copy-paste the data and run the analysis using MS Excel. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 What is the computed R square of the resulting multiple linear regression and its interpretation?
You generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=60.71x+33.51y=60.71x+33.51and the r2=0.1764r2=0.1764.What is the correlation coefficient for this data set?r =
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. a. Predict the sales next month for an employee with 2.5 years of experience. The predicted sales is 8.6 cars. b. Compute the coefficient of determination and interpret its meaning. The coefficient of determination is 0.234 Therefore, about _________% of the variation in monthly sales is explained by the years of sales experience. (Type an integer or decimal rounded to one decimal place as needed.)
Please help me! I have no idea where to even start. Conclude that the mean height is not equal to 64 inches because the P-value is less than 0.05. a. Find the correlation coefficient between the height and the weight. b. Construct the equation of the regression line. c. Predict the weight of a student who is 68 inches tall.
Prev The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density 61 62 68 69 40 357 350 343 340 315 Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Table Copy Data Next
The table below gives the number of hours spent unsupervised each day as well as the overall grade averages for seven randomly selected middle school students. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting the overall grade average for a middle school student based on the number of hours spent unsupervised each day. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Hours Unsupervised 0.5 1.5 2.5 3 4 4.5 6 Overall Grades 89 86 81 79 72 67 62 Table Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.
a ift = The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, bo + b₁x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. tab ** Answer How to enter your answer (opens in new window) Step 2 of 6: Find the estimated y-Intercept. Round your answer to three decimal places. esc 1945 ! 1 q alt a Z ebook x360 ng from any angle. @ 2 W S →>> X # 3 e d C $ 4 C r f Age Bone Density 359 % 5 V t g 36 51 63 66 70 357 328 314 310 Oll A 6 b y hp h & 7 O n u j * 8 N O i m ( 9 k O 100- 4 Tables ctrl { [ Keypad Keyboard Shortcuts Previous step answers Submit Answer D + = 11 : 90 ; ? Copy Data O SEAR Dec 2 Table ] USE YOUR SMARTPHONE FOR…

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