An Introduction to Statistical Methods and Data Analysis
7th Edition
ISBN: 9781305269477
Author: R. Lyman Ott, Micheal T. Longnecker
Publisher: Cengage Learning
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If a scatterplot is created in excel, and a line of regression is fit along with a derived functional form, what does it mean to describe and interpret them? What conclusions would be made about relationships between two recorded variables?
You spilled water on your calculations from (a) and can't remember what your estimated regression parameters are. But you do have two possible estimated errors for each of your initial four observations:
** had to resubmit this question because the first time the data was duplicated and reflected incorrectly.
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, yˆ=b0+b1xy^=b0+b1x, 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
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5.5
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Overall Grades
96
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68
64
**Please circle the answer for each step so I don't get confused. Thanks in advance for helping me with the breakdown and notes**
Step 1 of 6 :
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Chapter 11 Solutions
An Introduction to Statistical Methods and Data Analysis
Ch. 11.9 - Prob. 1ECh. 11.9 - Refer to Exercise 11.1.
Plot the equation in the...Ch. 11.9 - Use the data given here to answer the following...Ch. 11.9 - Prob. 4ECh. 11.9 - Use the output from Minitab for these data to...Ch. 11.9 - A food processor was receiving complaints from its...Ch. 11.9 - An online retailer needs to manage the amount of...Ch. 11.9 - A manufacturer of cases for sound equipment...Ch. 11.9 - Refer to the data of Exercise 11.7. a. Calculate a...Ch. 11.9 - Refer to the data of Exercise 11.8.
Calculate a...
Ch. 11.9 - Refer to the data of Exercise 11.8.
Calculate a...Ch. 11.9 - Athletes are constantly seeking measures of the...Ch. 11.9 - A firm that prints automobile bumper stickers...Ch. 11.9 - A chemist is interested in determining the weight...Ch. 11.9 - Refer to Exercise 11.22 to complete the following....Ch. 11.9 - Prob. 40ECh. 11.9 - A survey of MBA, graduates of a business school...Ch. 11.9 - Refer to the data in Exercise 11.44.
Determine the...Ch. 11.9 - There has been an increasing emphasis in recent...Ch. 11.9 - An air conditioning company responds to calls...Ch. 11.9 - Refer to Exercise 11.61. a. Calculate the...Ch. 11.9 - Refer to Exercise 11.61.
Test for lack of fit for...Ch. 11.9 - Refer to Exercise 11.61.
Compute the standard...Ch. 11.9 - Prob. 93SE
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardIf your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?arrow_forward
- According to World Health Organization (WHO), the recommended limit for a noise level inside a classroom is 35 dBA. However, nine out of ten schools fail to meet this recommendation. A researcher wishes to conduct a study relevant to the prior information, but as a gap, he decides to include the area (in square meters) of every classroom and how it could possibly affect the resulting noise level. He selects 17 classrooms at random, and the noise levels are recorded in the next slide. a. Find the regression equation and construct the scatter plot diagram. b. Predict the noise level if a classroom has an area of 85.97 m2 . c. Calculate the coefficient of determination and interpret the findings. d. Calculate the coefficient of alienation and interpret the findings. Use Excelarrow_forwardIf I want to estimate the regression of a model by using OLS on Eveiws , and I chose the "keep it as general as possible" approach, what tests can I apply through the estimation and inference process to validate the model and the variables?arrow_forwardIS the following statment true or false, please explain why For each x term in the multiple regression equation, the corresponding β is referred to as a partial regression coefficient.arrow_forward
- The following results are from data concerning the amount withdrawn from an ATM machine based on the amount of time spent at the ATM machine (SECONDS) and the gender, FEMALE (dummy variable = 1 for females and = 0 for males) and an interaction term, SECONDS*FEMALE Based on the regression results, if a male and female each spend the same amount of time at the ATM machine (say 27 seconds), how much more (or less) will a male withdraw? (if a male withdraws more then your answer should be a positive number and if a male withdraws less then your answer should be a negative number? (please express your answer using 1 decimal places)arrow_forwardWhat is the effect of this violation on the regression model? "The number of observations n is less than or equal to the number of parameters to be estimated"arrow_forwardA zoologist selected 12 black bears in a Canadian habitat at random to examine the relationship between the age in years, xx, and the weight in tens of pounds, yy. The 95 percent confidence interval for estimating the population slope of the linear regression line predicting weight in tens of pounds based on the age in years is given by 1.272±0.5701.272±0.570. Assume that the conditions for inference for the slope of the regression equation are met. Which of the following is the correct interpretation of the interval? A)We are 95 percent confident that the mean increase in the weight of a black bear for each one-year increase in the age of the bear is between 7.0 and 18.4 pounds. B)We are 95 percent confident that an increase of one year in the age of an individual black bear will result in an increase in the black bear’s weight of between 7.0 and 18.4 pounds. C)We are 95 percent confident that for every one-year increase in the age of black bears in the sample,…arrow_forward
- What is the slope of the least-squares regression line for these data? Carry your intermediate computations to at least four decimal places and round your answer to at least three decimal places.arrow_forwardIf the standard error of the estimate for a regression model fitted to a large number of paired observations is 1.75, approximately 95% of the residuals would lie within ______. −3.50 and +3.50 −1.75 and +1.75 −0.95 and +0.95 −0.68 and +0.68 −0.97 and +0.97arrow_forwardWould I use the regression line to predict Y from X ? And what is the pattern of the scatterplot?arrow_forward
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