The data in the accompanying table represent the annual rates of return for various stocks. If you only wish to invest in two stocks, which two would you select if your goal is to have low correlation between the= two investments? Which two would you select if your goal is to have one stock go up when the other goes down?Click the icon to view the table of annual rates of returns.If your goal is to have low correlation between the two investments, you should selectView an example Get more help.Annual Rates of ReturnsYear1234567891011Stock A-0.4800.0460.1260.316-0.2580.4960.085-0.044-0.011-0.181-0.316OLStock B0.0910.1060.137-0.080-0.032-0.0690.081-0.0190.0690.0790.276PrintStock C0.0271.3200.184-0.0640.014-0.1270.087-0.0450.1460.0790.221Done***Stock D-0.1210.4910.1490.057-0.0920.10.084-0.0360.068-0.0080.06since the linear correlation coefficient for these two stocksO- X4Clear allCheck answer0 20O6:21 PM12/12/2022

Introduction The correlation shows the relationship b/w 2 variables.

Answered: The data in the accompanying table…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

In addition to therapy, anti-depressant drugs are used in the treatment of depression. The data below are from a study comparing two anti-depressant drugs. A baseline measurement for symptomatic behavior for depression is taken. After treatment with medication, another measurement taken. The data given in the table is for improvement which is for the reduction in symptomatic behavior.
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
Determine if correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship. Your daily calorie intake and weight. (a) Positive (b) Negative (c) No correlation
Give an example of two variables that have a positive linear correlation. Give an example of two variables that have a negative linear correlation. Give an example of two variables that have no correlation. Below is the height in inches and weight in pounds of eleven individuals Height, x 62 63 66 68 70 72 73 74 74 75 75 Weight, y 195 190 250 220 250 255 260 275 280 295 300 x = 65 inches x = 69 inches x = 71 inches
Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y= -71.12x + 92.48 and the r= -0.571
Give an example of two variables that you would expect to have a correlation close to or equal to -1. Give an example of two variables that you would expect to have a correlation close to or equal to 0. Remember that survey question you wrote? Take the class responses to your survey as data related to the one variable of your question. Now, take the list of responses from the survey question that one of your classmates wrote. Write down both lists of data. (If one sample size happens to be different from the other, cut the larger sample size down to that of the smaller sample size.) Calculate the correlation between the two variables. Describe the linear relationship between these two variables. (data for number 3) How many cars have you had so far in your lifetime? 0,1,1,1,2,2,2,2,3,3,3,3,4,4,5,6,6,7,10. How many days per week do you exercise? 0,0,0,1,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6
The marketing research department of a large company knows that the company's monthly sales are influenced by the way in which it spends money on marketing. For example, monthly expenditures such as the ones listed below are known to have an effect on y, the company's total monthly sales (in millions of dollars). X 1 = money spent on television advertising (in 1000's of dollars) X2 = money spent on promotion (i.e., free samples) X3 money spent on newspaper advertising (in 1000's of dollars) = average discounts offered to retail outlets (in %) Using data from the previous 16 months, the company decides to collect data on 2 of the independent variables to use in a multiple regression model for estimating monthly sales. If the R for this model is 0.81, fill in the missing entries in the ANOVA table associated with this model. Do all calculations to at least three decimal places.
L4Q6.What correlation can be observed between x and y in the given figure?
Suppose that two variables, x and y, have a correlation coefficient of −0.77. Which of the following statements are true? You must make a selection for each option. Click once to place a check mark for correct answers and click twice to empty the box for the wrong answers. check all that apply There is a strong relationship between these two variables. As x increases, y decreases. The variables have a negative linear relationship. As x increases, y increases. There is a weak relationship between these two variables.
An LCBO employee compares the relationship between the price of 6 different vintage bottles of wine, and the number of those bottles that have been purchased in the last 3 months to see if there is a correlation between the number of bottles purchased and the price of the bottle. Number of Bottles of Wine Purchased in the Price of Wine Bottle ($) Last 3 Months 44 18 93 65 82 56 25 60 15 30 20 40

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS