Determine if the correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship. a) The average selling price of a model of car and the cost of a loaf of bread on a given day b) The number of crimes committed in an area and the selling price of homes in that area c) The number of pets owned by a family and the cost of their vet bills

Determine if the correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship. a) The average selling price of a model of car and the cost of a loaf of bread on a given day b) The number of crimes committed in an area and the selling price of homes in that area c) The number of pets owned by a family and the cost of their vet bills

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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3. The speed (in miles per hour) of 8 vehicles and their braking distance (in feet) when stopping on a dry surface speed, x braking distance, y 20 30 40 50 50 60 65 70 55 72 75 110 138 162 193 225 type of correlation: Conclusion
OA. The scatterplot indicates there is a negative, strong, linear relationship between Median Salary and Annual Sales. OB. The scatterplot indicates there is a negative, weak, linear relationship between Median Salary and Annual Sales. OC. The scatterplot indicates there is a positive, strong, linear relationship between Median Salary and Annual Sales. OD. The scatterplot indicates there is a positive, weak, linear relationship between Median Salary and Annual Sales. OE. The scatterplot indicates there is no relationship between Median Salary and Annual Sales.
10. The direction of the points around the line in a scatter plot suggests the of the variables. D. variation/strength C. trend B. shape A. form 11. If the points on the scatter graph rise from left to right, then the variables involved have a correlation. D. zero C. positive A. moderate B. negligible of the points to the trend on a 12. The strength of the correlation is associated with the scatter plot. D. number C. form B. direction A. closeness 13. Noah noticed that the points on a scatter plot follow a trend rising from right to left. He also noticed that the points are plotted closely around the trend line. What is the correlation of the variables involved? A. strong negative B. strong positive C. weak negative D. weak positive 14. If the points on the scatter plot fall almost in line, then the variables are said to have correlation. D. strong A. negative C. positive B. perfect 15. Joan noticed that the high value of one variable corresponds to high value of the second variable or…
6. Which of these relationships would be better described with a Spearman's rank coefficient than with a Pearson's coefficient? a. The association between income and educational attainment (measured in years of school) b. The association between hours of sleep and score on an exam C. The association between years aged and price of wine d. The association between ice cream sales and crime rates e. The association between number on NY Times Best Seller List and copies of book sold
11. Decide whether the following variables are positively correlated, negatively correlated, or uncorrelated. a. Your grades and the number of hours per week you study b. Your grades and the number of hours per week you party c. Your grades and the number of cookies per week you eat d. The daily average temperature and sales of cell phones e. The daily average temperature and sales of overcoats f. The daily average temperature and sales of shorts
A biscuit production manager wants to investigate the linear relationship between the number of items produced and the production cost. To pursue his/her objective, the manager recorded the data on the number of items produced per day and the production cost per day (in thousands of Malaysian Ringgit) as shown in Table 3 Table 3 Days 1 2 4 6. 7 8 10 11 Number of items, (x) 26 67 86 17 10 44 53 40 77 80 20 20 Production cost, (y) 21 60 69 47 50 | 98 39 55 85 104 37 20 a) Name the TWo (2) most popular correlation coefficients. OPearson Oz-table OT-table Ochi-square Ospearman b) Calculate the correlation coefficient, r. ху x2 y2 26 21 676 44 60 2640 1936 3600 53 69 3657 2809 4761 47 1880 2209 77 50 3850 5929 2500 80 98 7840 6400 9604 20 39 780 400 1521 20 55 1100 400 3025 67 5695 4489 7225 86 104 8944 7396 10816 17 37 629 289 1369 10 20 200 100 400 E y² = Σχ ΣΥ- Σχy- Ex? = || || **Answer should be up to 4 decimal place (dp) r = c) Based on the correlation coefficient, robtained, make a…
2.4 terlashow Worksheet 4.5 3. A car dealership is analyzing the changes in its monthly sales. They sold 40 cars in March, 55 in April, 61 in May, 29 in June, 63 in July, and 40 in August. Create line graph that represents this data. emait yerty bisz Sanco efimy svib AI 360 bar & svart 0.160 and to toloo er viunebi of bades new sinobuta SA 160 salsa.nolo3 1aritons esw 163 tiert bisz gniniemen sdt bns as old sved Ofic nong saved stab aid atangan ter dos
Seventy-six Starbucks food items were analyzed for the calorie and carbohydrate content. We used linear regression to explore the relationship between the number of calories and amount of carbohydrates (in grams) Starbucks food menu items contain. The estimated regression equation with carbohydrates as the response variable and the calories as the explanatory variable is ŷ = 8.94 + 0.11x, and summary statistics of the two variables is provided below. variable min Q1 median Q3 max mean sd n missing calories 80 300 350 420 500 338.8 105.4 77 carbohydrates 16 31 45 59 80 44.9 16.6 77
3. If there is a linear, strong, and positive relationship between the scores on two tests, we should conclude that A. Scoring high on one test causes an individual to score high on the other test. B. high scores on one test are associated with low scores on the other test. C. as one test score goes down, the other test score goes up. D. low scores on one test are associated with low scores on the other test. E. the value of r must be close to 0.
3. Using data in question 6, determine whether there is enough evidence to conclude that the type II has higher strength than type I? Use a pooled t-test with a = 0.05. 1. Identify the parameters 2. Null Hypothesis 3. Alternative Hypothesis 4. Test Statistic 5. Rejection Region 6. Conclusion
2. An aerobic exercise instructor submitted to the shipping company the data given in the following table, which shows the recommended maximum exercion heart rate for individuals of the given ages. See table below. If the Chief engineer is 62 years old, predict. naximum exercise heart rate. Age (x years) Maximum heart rate (y beats per minute) 20 40 60 170 153 136 A. What is the coefficient of correlation of the age and the maximum rate of the chief engineer? a. -100 b. 100 C. -0.99 d. 0.65
1. Learn by Doing (page 68): In this activity we have data from 21 female college students. Forearm length in inches is the explanatory variable. Height in inches is the response variable. The line is a good summary of the linear pattern in the data. a. Based on the graph of this line, which is the best prediction of the height of a woman with a forearm of 11 inches? i. 64.5 inches ii. 68 inches iii. 68.75 inches iv. just under 72 inches 74 72 70 68 66 64 62- 60 b. The equation of this line is: Predicted height = 39 + 2.7 * forearm length. Use the equation of the line to predict the height of a woman with a 10-inch forearm. 58- 56 %3D 10.5 forearm (inches) 8.0 8.5 9.0 9.5 10.0 11.0 11.5 12.0 12 height (inches)