coefficients

What effect does an outlier have on a correlation coefficient? Would it increase, decrease or stay the same?

The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 27 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4500 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 27 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. Minitab output The linear correlation coefficient is. (Round to three decimal places as needed.) The regression equation is Highway = 50.4- 0.00535 Weight %3D Predictor Сoef SE Coef T Constant 50.383 2.732 17.75 0.000 Weight - 0.0053502 0.0007856 -7.55 0.000 S= 2.17876 R-Sq = 65.1% R-…

An ecologist is interested in exploring the relationship between pollination rate and the number of bees present at apple orchards. The relationship is: (Pollination rate) = 372.6 + 13.5 x (bees) with r = 0.80. The best interpretation of the correlation coefficient is: (pick one) 1. 64% of the variability in pollination rate observed at apple orchards is explained by the relationship with the number of bees 2. the correlation between pollination rate and number of bees is 0.64 3. 80% of the variability in number of bees at apple orchards is explained by the relationship with the pollination rate 4. the correlation between pollination rate and number of bees is 0.80

For a sample of eight bears, researchers measured the distances around the bears' chests and weighed the bears. Minitab was used to find that the value of the linear correlation coefficient is r = 0.862. Using a = 0.05, determine if there is a linear correlation between chest size and weight. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? Click here to view a table of critical values for the correlation coefficient. a. Is there a linear correlation between chest size and weight? O A. No, because the absolute value of r exceeds the critical value of 0.707. O B. Yes, because r falls between the critical values of -0.707 and 0.707. O C. Yes, because the absolute value of r exceeds the critical value of 0.707. O D. The answer cannot be determined from the given information. b. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? (Round to three decimal…

The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 26 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 3000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 26 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Minitab output The regression equation is Highway = 50.3 -0.00539 Weight Predictor Coef SE Coef Constant 50.288 2.998 Weight -0.0053868 0.0007773 |S=2.11773 R-Sq=64.0% R-Sq(adj) = 60.9% Predicted Values…

Fifty-four wild bears were anesthetized, and their weights and chest sizes were measured. Results are showing in the graph below. IS there sufficient evidence to support the claim that there is a linear correlation between weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Correlation Results Correlation coeff r:0.963141 Critical r ±0.2680855 P-value (two-tailed) 0.000

Once the correlation coefficient is known, how can we find the amount of the shared variance?

Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support Correlation Results the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that Correlation coeff, r: 0.959614 a measured chest size can be used to predict the weight? Use a significance level of = 0.05. Critical r: +0.2680855 P-value (two tailed): 0.000 Но: Р H1:P (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) O A. There is one critical value at r= . B. There are two critical values at r= ± Is there sufficient evidence to support the claim that there is a linear correlation between…

In a study of the stability of IQ scores, a large group of individuals is tested once at age 18 and again at age 35. The following results are obtained. At age 18: average score = 100, SD = 15 At age 35: average score = 100, SD = 15 The correlation coefficient between scores at age 18 and 35 is 0.80 and the scatter plot is football shaped. What percent of the individuals with a score of 115 at age 18 score more than 100 at age 35? Fill in the blank with a number between 0 and 100 to represent the percentage. (Do not enter the % sign.) Don't worry about rounding; any correctly rounded answer will receive full credit.