The correlation coefficient r=0.15, is given for a sample of n= 13 data points. Use the a = 0.05column in the figure to the right to determine whether or not we may conclude that a correlationdoes exist in the population. (Using the a = 0.05 column there is a probability of 0.05 that thevariables are not really correlated in the population and our results could be attributed to chance.Ignore this possibility when concluding whether or not there is a correlation in the population.)a=.050.950=.054.19 0.45650.87820 0.44422 0.42327 0.3816.0.8110.75480.707320.3490.3250.30490.66637100.63242Choose the correct answer below.110.602470.288120.576520.273O A. Correlation does exist130.553620.250140.53272 0.232O B. Correlation does not exist1516170.5148292 0.205102 0.1950.2170.4970.482180.468O TimMAR18MacBook Air

From the given table of critical values, we go for n = 13 and alpha = 0.05, we get Critical value =…

Answered: The correlation coefficient r=0.15, is…

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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Serial correlation, also known as autocorrelation, describes the extent to which the result in one period of a time series is related to the result in the next period. A time series with high serial correlation is said to be very predictable from one period to the next. If the serial correlation is low (or near zero), the time series is considered to be much less predictable. For more information about serial correlation, see the book Ibbotson SBBI published by Morningstar.A company that produces and markets video games wants to estimate the predictability of per capita consumer spending on video games in a particular country. For the most recent 7 years, the amount of annual spending per person per year is shown here. Original Time Series Year 1 2 3 4 5 6 7 $ per capita 32.27 34.06 37.83 43.32 44.62 49.67 51.83 (a) To construct a serial correlation, we use data pairs (x, y) where x = original data and y = original data shifted ahead by one time period. Construct the data…
Which of the following conclusions might be a conclusion that a researcher would make if he/she had just rejected the null hypothesis? there is a correlation in the population all brands are equally preferred in the population The treated population scores the same as the general population There is no difference between the population with the drug and the population without the drug
Following Is a random sample of three (x, y) pairs of data polnts (10, 100), (15, 50) and (6, 25). The correlation between x and y is a. 0.28 O b. 0.82 1.00 Od. 50
2. If the correlation coefficient is 0.930, what is the unexplained variation? A 86.5% B. 93% C. 7% D. 13.5%
Which of the following tests is appropriate, if we want to determine the relationship between workout duration (minutes) and the distance (kilometers).A. Two-sample t-testB. Kendall correlationC. Pearson correlationD. Spearman correlation
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To examine the linear correlation between adult age and weight, data was collected from 9 adults. See the table below. Age Weight (Years) (pounds) 26 203 28 245 29 141 34 139 39 199 40 194 41 137 50 181 52 197 Does this result suggest that the correlation is statistically significant? Use a = 0.01. Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the built- in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, use the rounded STS. 1. Select the correct statement: O f the correlation is found to be statistically significant, that means that changes in æ cause changes in y O Even if the correlation is found to be statistically significant, that does not necessarily mean that changes in æ cause changes in y
The accompanying data are x = advertising share and y = market share for a particular brand of soft drink during 10 randomly selected years. x 0.104 0.072 0.072 0.077 0.086 0.047 0.060 0.050 0.070 0.052 y 0.137 0.127 0.120 0.086 0.079 0.076 0.065 0.059 0.051 0.039 b)Calculate the equation of the estimated regression line. (Round your answers to four decimal places.) d)Calculate a point estimate of ?e. (Round your answer to five decimal places.)
The scatterplot below shows the relationship between two random variables X and Y. (a) Is the correlation a good metric for describing the relationship between X and Y for these data? Why or why not? Regardless of your answer suppose you calculated the sample correlation between X and Y and found that r = -0.15. Explain in one sentence what this means. (b) If, as noted in (a), r = -0.15 then what is the value of the correlation between 2X and 5Y? (c) Based on (b) draw your best approximation to the least squares regression line that fits the data above. Also, make a rough sketch of the corresponding residual plot.
With a very small sample, a single point can have a large influence on the magnitude of a correlation. For the following data set, X Y 0 1 10 3 4 1 8 2 8 3 Part A. OPTIONAL BUT HELPFUL: Sketch a graph showing the X, Y points.Part B. OPTIONAL BUT HELPFUL: Estimate the value of the Pearson correlation.Part C. Compute the Pearson correlation.Part D. Now we will change the value of one of the points. For the first individual in the sample (X = 0 and Y = 1), change the Y value to Y = 6. What happens to the graph of the X, Y points? What happens to the Pearson correlation? Compute the new correlation. This time just choose the values of the correlation for parts C and D respectively A) (C) .875; (D) .535 B)(C) .875; (D) -.535 C) C) -.875; (D) .535 D) (C) -.875; (D) -.535
A study was done to look at the relationship between number of lovers college students have had in their lifetimes and their GPAs. The results of the survey are shown below. Lovers 4 6 GPA 0 2.9 2.9 3.5 3 0 3.4 3.3 140 8 1.7 2 3.3 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: H₁: The p-value is: 6 6 2.4 1.9 Round to 2 decimal places. (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically insignificant evidence to conclude that there is a correlation between the number of lovers students have had in their lifetimes and their GPA. Thus, the use of the regression line is not appropriate. O There is statistically insignificant evidence to conclude that a student who has had more lovers will have a lower GPA than a student who has had fewer lovers. O There is statistically significant evidence to conclude that…
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