Essential Statistics
2nd Edition
ISBN: 9781259570643
Author: Navidi
Publisher: MCG
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Chapter 11.3, Problem 26E
a.
To determine
Find the least-square regression line for predicting the rate of evaporation y from outdoor temperature x.
b.
To determine
Construct the 99% confidence interval for the slope coefficient.
c.
To determine
Test the significance of rate of evaporation in predicting the outdoor temperature at 5% level of significance.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Computer output from a least-squares regression analysis based on a sample of size 17 is shown in the table.
Term
COEFCOEF
SE CoefSE Coef
TT
Constant
7.43
0.59
12.59
xx
5.65
1.14
6.45
Assuming all conditions for inference are met, which of the following defines a 95 percent confidence interval for the slope of the least-squares regression line?
Computer output from a least-squares regression analysis based on a sample of size 17 is shown in the table.
Term
COEFCOEF
SE CoefSE Coef
TT
Constant
7.43
0.59
12.59
xx
5.65
1.14
6.45
Assuming all conditions for inference are met, which of the following defines a 95 percent confidence interval for the slope of the least-squares regression line?
5.65±1.96(1.14)5.65±1.96(1.14)
A
5.65±2.120(1.14)5.65±2.120(1.14)
B
5.65±2.131(1.14)5.65±2.131(1.14)
C
7.43±2.120(0.59)7.43±2.120(0.59)
D
7.43±2.131(0.59)
E
A linear regression model was fit to a set of data containing 18 observations. The computer output of the regression analysis is shown in the table.
Term
CoefCoef
SE CoefSE Coef
TT
Constant
12.00
5.43
2.210
xx
0.694
0.241
2.880
Assume the conditions for regression are met. Which of the following defines the margin of error when a 95 percent confidence interval for the slope of the least-squares regression line is calculated?
(1.75)(0.241)
A
(1.75)(0.694)
B
(1.96)(0.241)
C
(2.12)(0.241))
D
(2.12)(0.694)
E
Chapter 11 Solutions
Essential Statistics
Ch. 11.1 - Prob. 1CYUCh. 11.1 - Prob. 2CYUCh. 11.1 - Prob. 3CYUCh. 11.1 - Prob. 4CYUCh. 11.1 - Prob. 5CYUCh. 11.1 - Prob. 6CYUCh. 11.1 - Prob. 7CYUCh. 11.1 - Prob. 8CYUCh. 11.1 - Prob. 9ECh. 11.1 - Prob. 10E
Ch. 11.1 - Prob. 11ECh. 11.1 - Prob. 12ECh. 11.1 - Prob. 13ECh. 11.1 - Prob. 14ECh. 11.1 - Prob. 15ECh. 11.1 - Prob. 16ECh. 11.1 - Prob. 17ECh. 11.1 - Prob. 18ECh. 11.1 - Prob. 19ECh. 11.1 - Prob. 20ECh. 11.1 - Prob. 21ECh. 11.1 - Prob. 22ECh. 11.1 - Prob. 23ECh. 11.1 - Prob. 24ECh. 11.1 - Prob. 25ECh. 11.1 - Prob. 26ECh. 11.1 - Prob. 27ECh. 11.1 - In Exercises 25–30, determine whether the...Ch. 11.1 - Prob. 29ECh. 11.1 - Prob. 30ECh. 11.1 - Prob. 31ECh. 11.1 - Prob. 32ECh. 11.1 - 33. Pass the ball: The NFL Scouting Combine is an...Ch. 11.1 - 34. Carbon footprint: Carbon dioxide (CO2) is...Ch. 11.1 - 35. Foot temperatures: Foot ulcers are a common...Ch. 11.1 - Prob. 36ECh. 11.1 - Prob. 37ECh. 11.1 - Prob. 38ECh. 11.1 - Prob. 39ECh. 11.1 - Prob. 40ECh. 11.1 - Prob. 41ECh. 11.1 - Prob. 42ECh. 11.1 - Prob. 43ECh. 11.2 - 1. The following table presents the percentage of...Ch. 11.2 - 2. At the final exam in a statistics class, the...Ch. 11.2 - 3. For each of the following plots, interpret the...Ch. 11.2 - Prob. 4CYUCh. 11.2 - Prob. 5ECh. 11.2 - In Exercises 5–7, fill in each blank with the...Ch. 11.2 - Prob. 7ECh. 11.2 - Prob. 8ECh. 11.2 - In Exercises 8–12, determine whether the statement...Ch. 11.2 - Prob. 10ECh. 11.2 - Prob. 11ECh. 11.2 - Prob. 12ECh. 11.2 - Prob. 13ECh. 11.2 - Prob. 14ECh. 11.2 - Prob. 15ECh. 11.2 - Prob. 16ECh. 11.2 - Prob. 17ECh. 11.2 - Prob. 18ECh. 11.2 - Prob. 19ECh. 11.2 - Prob. 20ECh. 11.2 - Prob. 21ECh. 11.2 - Prob. 22ECh. 11.2 - Prob. 23ECh. 11.2 - Prob. 24ECh. 11.2 - Prob. 25ECh. 11.2 - Prob. 26ECh. 11.2 - 27. Blood pressure: A blood pressure measurement...Ch. 11.2 - Prob. 28ECh. 11.2 - 29. Interpreting technology: The following display...Ch. 11.2 - Prob. 30ECh. 11.2 - Prob. 31ECh. 11.2 - Prob. 32ECh. 11.2 - Prob. 33ECh. 11.2 - Prob. 34ECh. 11.2 - Prob. 35ECh. 11.3 - Prob. 1CYUCh. 11.3 - Prob. 2CYUCh. 11.3 - Prob. 3CYUCh. 11.3 - Prob. 4CYUCh. 11.3 - Prob. 5CYUCh. 11.3 - Prob. 6CYUCh. 11.3 - Prob. 7ECh. 11.3 - Prob. 8ECh. 11.3 - Prob. 9ECh. 11.3 - Prob. 10ECh. 11.3 - Prob. 11ECh. 11.3 - Prob. 12ECh. 11.3 - Prob. 13ECh. 11.3 - Prob. 14ECh. 11.3 - Prob. 15ECh. 11.3 - Prob. 16ECh. 11.3 - Prob. 17ECh. 11.3 - Prob. 18ECh. 11.3 - Calories and protein: The following table presents...Ch. 11.3 - Prob. 20ECh. 11.3 - Butterfly wings: Do larger butterflies live...Ch. 11.3 - Blood pressure: A blood pressure measurement...Ch. 11.3 - Prob. 23ECh. 11.3 - Prob. 24ECh. 11.3 - Getting bigger: Concrete expands both horizontally...Ch. 11.3 - Prob. 26ECh. 11.3 - Prob. 27ECh. 11.3 - Prob. 28ECh. 11.3 - Prob. 29ECh. 11.3 - Prob. 30ECh. 11.3 - Prob. 31ECh. 11.4 - Prob. 1CYUCh. 11.4 - Prob. 2CYUCh. 11.4 - Prob. 3ECh. 11.4 - Prob. 4ECh. 11.4 - Prob. 5ECh. 11.4 - Prob. 6ECh. 11.4 - Prob. 7ECh. 11.4 - Prob. 8ECh. 11.4 - Prob. 9ECh. 11.4 - Prob. 10ECh. 11.4 - Calories and protein: Use the data in Exercise 19...Ch. 11.4 - Prob. 12ECh. 11.4 - Butterfly wings: Use the data in Exercise 21 in...Ch. 11.4 - Prob. 14ECh. 11.4 - Prob. 15ECh. 11.4 - Prob. 16ECh. 11.4 - Prob. 17ECh. 11.4 - Prob. 18ECh. 11.4 - Prob. 19ECh. 11.4 - Prob. 20ECh. 11.4 - Prob. 21ECh. 11 - Prob. 1CQCh. 11 - Prob. 2CQCh. 11 - Prob. 3CQCh. 11 - Prob. 4CQCh. 11 - Prob. 5CQCh. 11 - Prob. 6CQCh. 11 - Prob. 7CQCh. 11 - Prob. 8CQCh. 11 - Prob. 9CQCh. 11 - Prob. 10CQCh. 11 - Prob. 11CQCh. 11 - Prob. 12CQCh. 11 - Prob. 13CQCh. 11 - Prob. 14CQCh. 11 - Prob. 15CQCh. 11 - Prob. 1RECh. 11 - Prob. 2RECh. 11 - Prob. 3RECh. 11 - Prob. 4RECh. 11 - Prob. 5RECh. 11 - Prob. 6RECh. 11 - Prob. 7RECh. 11 - Prob. 8RECh. 11 - Prob. 9RECh. 11 - Prob. 10RECh. 11 - Prob. 11RECh. 11 - Prob. 12RECh. 11 - Prob. 13RECh. 11 - Interpret technology: The following TI-84 Plus...Ch. 11 - Prob. 15RECh. 11 - Prob. 1WAICh. 11 - Prob. 2WAICh. 11 - Prob. 3WAICh. 11 - Prob. 4WAICh. 11 - Prob. 5WAICh. 11 - Prob. 6WAICh. 11 - Prob. 7WAICh. 11 - Prob. 1CSCh. 11 - Prob. 2CSCh. 11 - Prob. 3CSCh. 11 - Prob. 4CSCh. 11 - Prob. 5CSCh. 11 - Prob. 6CSCh. 11 - Prob. 7CSCh. 11 - Prob. 8CSCh. 11 - Prob. 9CSCh. 11 - Prob. 10CSCh. 11 - Prob. 11CS
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- In the macro relation between GDP and FDI, Dr Mudenda obtained the following valuesfrom a Stata output: FDI coefficient of 0.45; t-statistic of 3; and covariance (GDP, FDI)value of 0.41. In literature, this relationship between GDP and FDI has generally beenestablished to be statistically significant. Answer the following questions:i) Calculate the variance of the FDI variable and explain its implicationii) Use the confidence interval approach to test whether FDI’s influence on GDP isstatically significant or not in Dr Mudenda’s study. Use 5% level which gives 1.96critical values.iii) What is the expected value of the p-values for studies that have been conductedin literature?arrow_forwardThe cost of making a batch of a certain product depends on the size of the batch, as shown by the following sample data: Cost $ 30 70 140 270 530 1010 2000 5100 size of the batch 1 5 10 25 50 100 250 500 a) Fit a straight line to said data, with the least squares method, use the lot size as the independent variable. b) Find a 95% confidence interval for alfa that can be interpreted as the fixed overhead cost of manufacture.arrow_forwardSuppose we are making predictions of the dependent variable y for specific values of the independent variable x using a simple linear regression model holding the confidence level constant. Let Width (C.I) = the width of the confidence interval for the average value y for a given value of x, and Width (P.I) = the width of the prediction interval for a single value y for a given value of x. Which of the following statements is true? Width (C.I) = 0.5 Width (P.I) Width (C.I) = Width (P.I) Width (C.I) > Width (P.I) Width (C.I) < Width (P.I)arrow_forward
- A researcher developed a regression model to predict the cost of a meal based on the summated rating (sum of ratings for food, decor,and service) and the cost per meal for 12 restaurants. The results of the study show that b1=1.4379 and Sb1=0.1397. a. At the 0.05 level of significance, is there evidence of a linear relationship between the summated rating of a restaurant and the cost of a meal? b. Construct a 95% confidence interval estimate of the population slope, β1. a. Determine the hypotheses for the test. Choose the correct answer below. A. H0: β1=0 H1: β1≠0 B. H0: β0≤0 H1: β0>0 C. H0: β1≤0 H1: β1>0 D. H0: β0≥0 H1: β0<0 E. H0: β1≥0 H1: β1<0 F. H0: β0=0 H1: β0≠0 Compute the test statistic. The test statistic is ? (Round to two decimal places as needed.) Determine the critical value(s). The critical value(s) is(are) ? (Use a comma to separate answers as needed.…arrow_forwardA geneticist conducted a hybridization experiment with peas, which resulted in offspring consisting of 410 peas with green pods and 150 peas with yellow pods. According to Mendel’s theory, 1/4 of the offspring peas should have yellow pods. Use a 0.05 significance level to test the claim that the proportion of peas with yellow pods is equal to 0.25.a. H0: ______________b. HA: ______________c. Type of hypothesis test: __________________d. Critical value: ___________e. Test statistic value: ____________f. P-value: ____________g. Decision: _____________________________h. Conclusion: _____________________________________________arrow_forward1. An article included a summary of findings regarding the use of SAT I scores, SAT II scores, and high school grade point average (GPA) to predict first-year college GPA. The article states that "among these, SAT II scores are the best predictor, explaining 17 percent of the variance in first-year college grades. GPA was second at 15.3 percent, and SAT I was last at 13.6 percent." If the data from this study were used to fit a least squares line with y = first-year college GPA and x = high school GPA, what would the value of r2 have been? r2 =_______ 2. A study was carried out to investigate the relationship between the hardness of molded plastic (y, in Brinell units) and the amount of time elapsed since the plastic was molded (x, in hours). Summary quantities include n = 15, SSResid = 1,237.628, and SSTo = 24,619.737. Calculate and interpret the coefficient of determination. (Round the coefficient of determination to four decimal places when written as a decimal and 2 decimal…arrow_forward
- Like father, like son: In 1906 , the statistician Karl Pearson measured the heights of 1078 pairs of fathers and sons. The following table presents a sample of 7 pairs, with height measured in inches, simulated from the distribution specified by Pearson. Father'sheight Son'sheight 65.4 66.0 73.6 74.9 68.3 68.3 66.7 68.8 69.1 71.8 70.7 71.0 69.3 71.4 Compute the least-squares regression line for predicting son's height ( y) from father's height (x). Round the slope and y-intercept values to at least four decimal places.arrow_forwardIs a baseball players' slugging percentage correlated to their strikeout percentage? A random sample of n=6n=6professional baseball players gave the following data (Source: baseball-reference.com) Slugging 0.396 0.42 0.323 0.078 0.473 0.467 Strikeouts 27 14.3 30.8 47.1 17.8 36.7 Find the least squares line if we consider slugging percengtage as the explanatory variable and strikeout percentage as the response variable. (Round the y-intercept and slope to 2 decimal places.)y^ = For a unit increase in slugging percentage, how much of a decrease Correct in strikeout percentage is predicted? (Round your answer to 2 decimal places.) What percentage of the variation in strikeout percentage (yy) can be explained by slugging percentage (xx) and the least squares line? (Round to the nearest percent.) p-value (Round to four decimal places)arrow_forwardBased on the sample data set: (0,0) ( 2,3) (3,3) (6,4) (9,8) A. Construct the 90% confidence interval for the slope B1 of the population regression line B. find the Coefficient of determination using the formula r2=B1SSxy / SSyy.arrow_forward
- A scatterplot of student height, in inches, versus corresponding arm span length, in inches, is shown below. One of the points in the graph is labeled A. If the point labeled A is removed, which of the following statements would be true? The slope of the least squares regression line is unchanged and the correlation coefficient increases. The slope of the least squares regression line is unchanged and the correlation coefficient decreases. The slope of the least squares regression line increases and the correlation coefficient increases. The slope of the least squares regression line increases and the correlation coefficient decreases. The slope of the least squares regression line decreases and the correlation coefficient increases.arrow_forwardThe table below shows the numbers of bushels of barley cultivated per acre for 12 one-acre plots of land for two different strains of barley, PHT-34 and CBX-21. PHT-34 CBX-21 43 55 49 46 47 43 38 44 47 45 45 49 50 47 46 59 46 52 46 49 45 48 43 51 Determine the minimum data value, the quartiles, and the maximum data value for the PHT-34 and CBX-21 data sets. PHT-34 CBX-21 min Q1 Q2 Q3 maxarrow_forwardwhich of the following individuals is likely to be excluded from a clinical trial? a-individual with other diseases besides the disease of interest b-an individual whose data is considered to be an outlier c-an individual of who is considered to be a minority d-an individual who will have difficulty complying trial protocols.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage Learning
Linear Algebra: A Modern Introduction
Algebra
ISBN:9781285463247
Author:David Poole
Publisher:Cengage Learning
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY