Match the following scatterplots to their correct correlation coefficients (r).1. r=-0.852. r=-0.403. r=04. r=0.505. r=0.906. r=0.99 Match the following scatterplots to their correct correlation coefficients (r).>

From the given information we match with correlation.

Answered: Match the following scatterplots to…

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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Match the following scatterplots to their correct correlation coefficients (r). 1. r= -0.852. r= -0.403. r= 04. r= 0.505. r= 0.906. r= 0.99
Please round all answers to 2 decimal places. Given the table below, use your calculator to find the Correlation Coefficient x3.44.69.3105.34.9y15.511.220.222.710.814.3 Put your answer here:
Suppose the correlation coefficient r=0.16 Find:a. The coefficient of determination r2= (round to 3 decimal places)b. The percentage of explained variation = % (round to 1 decimal place)c. The percentage of unexplained variation = % (round to 1 decimal place)
The table below lists the mean systolic blood pressure during surgery (mmHg) along with blood loss (ml). Use this table to answer the next three (3) questions . BP Blood Loss 95274 90 170 Strength of Relationship 125 352 105317 weak moderate 110 171 105 150 90 245 90 120 none none 1/4 * 1/2; 3/4 13. Does the correlation coefficient indicate a strong linear correlation ? ( A) Yes ( B) No 14. Approximately what blood loss would you predict for a blood pressure reading of 140 ( A) 319 (B) 363 ( C) 401 ( D) 635 15. Do these data provide sufficient evidence , at the 0.05 level of significance , to indicate that the two variables are indeed correlated ?
Which of the following is the most appropriate equation to model the data? ŷ = –10.89x + 0.85 ŷ = –0.85x + 10.89 ŷ = 10.89(0.85)x ŷ = 0.85(10.89)x
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…
Use the data in the table, which shows the average annual salaries (both in thousands of dollars) for public school principals and teachers in the U.S. for 11 years. Apply what you have learned in the previous tab to complete this graded lab questions. 1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the corelation coefficient is R and not R Teachers y Principalsx 77.8 43.7 78.4 43.8 80.8 45.0 R= 80.5 45.6, 2. Does the R value represent a positive, negative or no correlation between the salaries ol the teachers and principals? As teacher salaries increase, what happens to prinicipal salaries? 10 11 81.5 45.9 84.8 48.2 12 13 87.7 49,3 3. Write the equation of the regression line for the data below. The equation is y= 14 91.6 51.3 52.9 Teachers y 15 16 95.7 54.4 COD 54.2 =D0.5873x-2.0s07o R=0.995, 17 95.7 4. Use the regression equation that you found in exercise #3 to predict the average annual salary…
A veterinarian collects data about puppies in her practice. She makes a scatterplot with their age in days on the horizontal axis and weight in ounces (oz) on the vertical axis and sees that the scatterplot is football shaped. The average age of the puppies is 42 day, with an SD of 7 days. The average weight is 25 oz, with an SD of 5 oz. The correlation is moderately strong, with r = 0.7. 4. (a) The age of two puppies differ by 20 days. The difference in their weight is predicted to be oz. (b) The baseline prediction for the weight of puppies ignores their age and just uses the information from all puppies. The baseline predicted weight is oz and the RMS error for this prediction is o. (c) Suppose we converted the units of age from days to weeks. The average age is now weeks, with an SD of weeks. The correlation between age in weeks and weight in oz is now r =
Match the linear correlation coefficient to the scatter diagram. The scales on the x- and y-axis are the same for each scatter diagram. (a) r= 0.523, (b)r=1, (c) r=0.787 (a) Scatter diagram (b) Scatter diagram Explanatory (c) Scatter diagram II Explanatory .......... Explanatory Click to select your answer(s). 9ME acer
Match the correlation coefficients with their scatterplots. Select the letter of the scatterplot below which corresponds to the correlation coefficient. (Click on image for a larger view.) B < 1. r = -0.49 A 2. r = 0.97 D ✓ 3. r = 0.22 4. r = -0.74 A B D
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Match the following scatterplots to their correct correlation coefficients (r). 1. r=-0.85 2. r=-0.40 3. r=0 4. r=0.50 5. r=0.90 6. r=0.99