Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
8th Edition
ISBN: 9781464158933
Author: David S. Moore, George P. McCabe, Bruce A. Craig
Publisher: W. H. Freeman
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Question
Chapter 12, Problem 22E
(a)
To determine
To find: The fitted data and the residuals. Also, generate the
(a)
Expert Solution
Answer to Problem 22E
Solution: The residuals of the provided data is scattered symmetrically above and below the zero and there is no extreme outlier.
Explanation of Solution
Given: The data provided in the Facebook friends study as,
| Friends | Participant | Score |
| 102 | 1 | 3.8 |
| 102 | 2 | 3.6 |
| 102 | 3 | 3.2 |
| 102 | 4 | 2.4 |
| 102 | 5 | 4.8 |
| 102 | 6 | 3.0 |
| 102 | 7 | 4.2 |
| 102 | 8 | 3.6 |
| 102 | 9 | 3.2 |
| 102 | 10 | 3.0 |
| 102 | 11 | 4.8 |
| 102 | 12 | 3.4 |
| 102 | 13 | 4.8 |
| 102 | 14 | 3.0 |
| 102 | 15 | 4.6 |
| 102 | 16 | 2.8 |
| 102 | 17 | 6.0 |
| 102 | 18 | 2.8 |
| 102 | 19 | 5.2 |
| 102 | 20 | 3.2 |
| 102 | 21 | 4.2 |
| 102 | 22 | 2.2 |
| 102 | 23 | 5.0 |
| 102 | 24 | 4.8 |
| 302 | 25 | 5.0 |
| 302 | 26 | 5.2 |
| 302 | 27 | 5.6 |
| 302 | 28 | 2.6 |
| 302 | 29 | 3.8 |
| 302 | 30 | 4.8 |
| 302 | 31 | 5.6 |
| 302 | 32 | 4.8 |
| 302 | 33 | 6.4 |
| 302 | 34 | 4.8 |
| 302 | 35 | 4.4 |
| 302 | 36 | 6.0 |
| 302 | 37 | 3.8 |
| 302 | 38 | 4.8 |
| 302 | 39 | 4.6 |
| 302 | 40 | 6.0 |
| 302 | 41 | 5.0 |
| 302 | 42 | 3.0 |
| 302 | 43 | 4.4 |
| 302 | 44 | 5.4 |
| 302 | 45 | 5.4 |
| 302 | 46 | 4.6 |
| 302 | 47 | 5.6 |
| 302 | 48 | 5.8 |
| 302 | 49 | 4.2 |
| 302 | 50 | 4.8 |
| 302 | 51 | 5.0 |
| 302 | 52 | 5.2 |
| 302 | 53 | 4.2 |
| 302 | 54 | 5.0 |
| 302 | 55 | 5.8 |
| 302 | 56 | 5.6 |
| 302 | 57 | 3.8 |
| 502 | 58 | 4.6 |
| 502 | 59 | 4.0 |
| 502 | 60 | 4.8 |
| 502 | 61 | 3.0 |
| 502 | 62 | 2.0 |
| 502 | 63 | 5.8 |
| 502 | 64 | 5.6 |
| 502 | 65 | 4.4 |
| 502 | 66 | 4.4 |
| 502 | 67 | 5.6 |
| 502 | 68 | 4.6 |
| 502 | 69 | 5.6 |
| 502 | 70 | 3.0 |
| 502 | 71 | 5.6 |
| 502 | 72 | 3.6 |
| 502 | 73 | 6.8 |
| 502 | 74 | 3.2 |
| 502 | 75 | 4.8 |
| 502 | 76 | 4.6 |
| 502 | 77 | 5.4 |
| 502 | 78 | 4.8 |
| 502 | 79 | 4.8 |
| 502 | 80 | 5.4 |
| 502 | 81 | 3.6 |
| 502 | 82 | 4.8 |
| 502 | 83 | 3.8 |
| 702 | 84 | 3.2 |
| 702 | 85 | 3.6 |
| 702 | 86 | 5.8 |
| 702 | 87 | 1.2 |
| 702 | 88 | 3.8 |
| 702 | 89 | 5.4 |
| 702 | 90 | 3.6 |
| 702 | 91 | 3.4 |
| 702 | 92 | 5.0 |
| 702 | 93 | 5.2 |
| 702 | 94 | 3.6 |
| 702 | 95 | 2.6 |
| 702 | 96 | 7.0 |
| 702 | 97 | 4.4 |
| 702 | 98 | 4.8 |
| 702 | 99 | 5.2 |
| 702 | 100 | 5.4 |
| 702 | 101 | 3.6 |
| 702 | 102 | 1.0 |
| 702 | 103 | 5.0 |
| 702 | 104 | 5.0 |
| 702 | 105 | 6.0 |
| 702 | 106 | 4.2 |
| 702 | 107 | 5.8 |
| 702 | 108 | 3.2 |
| 702 | 109 | 5.4 |
| 702 | 110 | 6.4 |
| 702 | 111 | 4.4 |
| 702 | 112 | 3.0 |
| 702 | 113 | 6.0 |
| 902 | 114 | 4.2 |
| 902 | 115 | 4.6 |
| 902 | 116 | 3.0 |
| 902 | 117 | 2.6 |
| 902 | 118 | 5.2 |
| 902 | 119 | 5.2 |
| 902 | 120 | 1.6 |
| 902 | 121 | 5.0 |
| 902 | 122 | 4.4 |
| 902 | 123 | 5.0 |
| 902 | 124 | 3.6 |
| 902 | 125 | 4.2 |
| 902 | 126 | 5.0 |
| 902 | 127 | 3.4 |
| 902 | 128 | 3.6 |
| 902 | 129 | 5.0 |
| 902 | 130 | 3.2 |
| 902 | 131 | 2.4 |
| 902 | 132 | 4.8 |
| 902 | 133 | 3.6 |
| 902 | 134 | 4.2 |
Calculation:
Use Minitab to find the residuals, of the provided data as below:
Step1: Enter the provided data in the worksheet.
Step2: Select stat >ANOVA>one-way analysis of variance.
Step3: Select Score in the Response and Friends in the Factor.
Step4: Click on Graphs and select the Residual verses fitand then press OK.
Step5: Select Store residual and Store fit.
Step6: Press OK.
Theobtained output of fitted data and the residual stored in the data file as below:
| Friends | Participant | Score | RESI1 | FITS1 |
| 102 | 1 | 3.8 | -0.01667 | 3.816667 |
| 102 | 2 | 3.6 | -0.21667 | 3.816667 |
| 102 | 3 | 3.2 | -0.61667 | 3.816667 |
| 102 | 4 | 2.4 | -1.41667 | 3.816667 |
| 102 | 5 | 4.8 | 0.983333 | 3.816667 |
| 102 | 6 | 3.0 | -0.81667 | 3.816667 |
| 102 | 7 | 4.2 | 0.383333 | 3.816667 |
| 102 | 8 | 3.6 | -0.21667 | 3.816667 |
| 102 | 9 | 3.2 | -0.61667 | 3.816667 |
| 102 | 10 | 3.0 | -0.81667 | 3.816667 |
| 102 | 11 | 4.8 | 0.983333 | 3.816667 |
| 102 | 12 | 3.4 | -0.41667 | 3.816667 |
| 102 | 13 | 4.8 | 0.983333 | 3.816667 |
| 102 | 14 | 3.0 | -0.81667 | 3.816667 |
| 102 | 15 | 4.6 | 0.783333 | 3.816667 |
| 102 | 16 | 2.8 | -1.01667 | 3.816667 |
| 102 | 17 | 6.0 | 2.183333 | 3.816667 |
| 102 | 18 | 2.8 | -1.01667 | 3.816667 |
| 102 | 19 | 5.2 | 1.383333 | 3.816667 |
| 102 | 20 | 3.2 | -0.61667 | 3.816667 |
| 102 | 21 | 4.2 | 0.383333 | 3.816667 |
| 102 | 22 | 2.2 | -1.61667 | 3.816667 |
| 102 | 23 | 5.0 | 1.183333 | 3.816667 |
| 102 | 24 | 4.8 | 0.983333 | 3.816667 |
| 302 | 25 | 5.0 | 0.121212 | 4.878788 |
| 302 | 26 | 5.2 | 0.321212 | 4.878788 |
| 302 | 27 | 5.6 | 0.721212 | 4.878788 |
| 302 | 28 | 2.6 | -2.27879 | 4.878788 |
| 302 | 29 | 3.8 | -1.07879 | 4.878788 |
| 302 | 30 | 4.8 | -0.07879 | 4.878788 |
| 302 | 31 | 5.6 | 0.721212 | 4.878788 |
| 302 | 32 | 4.8 | -0.07879 | 4.878788 |
| 302 | 33 | 6.4 | 1.521212 | 4.878788 |
| 302 | 34 | 4.8 | -0.07879 | 4.878788 |
| 302 | 35 | 4.4 | -0.47879 | 4.878788 |
| 302 | 36 | 6.0 | 1.121212 | 4.878788 |
| 302 | 37 | 3.8 | -1.07879 | 4.878788 |
| 302 | 38 | 4.8 | -0.07879 | 4.878788 |
| 302 | 39 | 4.6 | -0.27879 | 4.878788 |
| 302 | 40 | 6.0 | 1.121212 | 4.878788 |
| 302 | 41 | 5.0 | 0.121212 | 4.878788 |
| 302 | 42 | 3.0 | -1.87879 | 4.878788 |
| 302 | 43 | 4.4 | -0.47879 | 4.878788 |
| 302 | 44 | 5.4 | 0.521212 | 4.878788 |
| 302 | 45 | 5.4 | 0.521212 | 4.878788 |
| 302 | 46 | 4.6 | -0.27879 | 4.878788 |
| 302 | 47 | 5.6 | 0.721212 | 4.878788 |
| 302 | 48 | 5.8 | 0.921212 | 4.878788 |
| 302 | 49 | 4.2 | -0.67879 | 4.878788 |
| 302 | 50 | 4.8 | -0.07879 | 4.878788 |
| 302 | 51 | 5.0 | 0.121212 | 4.878788 |
| 302 | 52 | 5.2 | 0.321212 | 4.878788 |
| 302 | 53 | 4.2 | -0.67879 | 4.878788 |
| 302 | 54 | 5.0 | 0.121212 | 4.878788 |
| 302 | 55 | 5.8 | 0.921212 | 4.878788 |
| 302 | 56 | 5.6 | 0.721212 | 4.878788 |
| 302 | 57 | 3.8 | -1.07879 | 4.878788 |
| 502 | 58 | 4.6 | 0.038462 | 4.561538 |
| 502 | 59 | 4.0 | -0.56154 | 4.561538 |
| 502 | 60 | 4.8 | 0.238462 | 4.561538 |
| 502 | 61 | 3.0 | -1.56154 | 4.561538 |
| 502 | 62 | 2.0 | -2.56154 | 4.561538 |
| 502 | 63 | 5.8 | 1.238462 | 4.561538 |
| 502 | 64 | 5.6 | 1.038462 | 4.561538 |
| 502 | 65 | 4.4 | -0.16154 | 4.561538 |
| 502 | 66 | 4.4 | -0.16154 | 4.561538 |
| 502 | 67 | 5.6 | 1.038462 | 4.561538 |
| 502 | 68 | 4.6 | 0.038462 | 4.561538 |
| 502 | 69 | 5.6 | 1.038462 | 4.561538 |
| 502 | 70 | 3.0 | -1.56154 | 4.561538 |
| 502 | 71 | 5.6 | 1.038462 | 4.561538 |
| 502 | 72 | 3.6 | -0.96154 | 4.561538 |
| 502 | 73 | 6.8 | 2.238462 | 4.561538 |
| 502 | 74 | 3.2 | -1.36154 | 4.561538 |
| 502 | 75 | 4.8 | 0.238462 | 4.561538 |
| 502 | 76 | 4.6 | 0.038462 | 4.561538 |
| 502 | 77 | 5.4 | 0.838462 | 4.561538 |
| 502 | 78 | 4.8 | 0.238462 | 4.561538 |
| 502 | 79 | 4.8 | 0.238462 | 4.561538 |
| 502 | 80 | 5.4 | 0.838462 | 4.561538 |
| 502 | 81 | 3.6 | -0.96154 | 4.561538 |
| 502 | 82 | 4.8 | 0.238462 | 4.561538 |
| 502 | 83 | 3.8 | -0.76154 | 4.561538 |
| 702 | 84 | 3.2 | -1.20667 | 4.406667 |
| 702 | 85 | 3.6 | -0.80667 | 4.406667 |
| 702 | 86 | 5.8 | 1.393333 | 4.406667 |
| 702 | 87 | 1.2 | -3.20667 | 4.406667 |
| 702 | 88 | 3.8 | -0.60667 | 4.406667 |
| 702 | 89 | 5.4 | 0.993333 | 4.406667 |
| 702 | 90 | 3.6 | -0.80667 | 4.406667 |
| 702 | 91 | 3.4 | -1.00667 | 4.406667 |
| 702 | 92 | 5.0 | 0.593333 | 4.406667 |
| 702 | 93 | 5.2 | 0.793333 | 4.406667 |
| 702 | 94 | 3.6 | -0.80667 | 4.406667 |
| 702 | 95 | 2.6 | -1.80667 | 4.406667 |
| 702 | 96 | 7.0 | 2.593333 | 4.406667 |
| 702 | 97 | 4.4 | -0.00667 | 4.406667 |
| 702 | 98 | 4.8 | 0.393333 | 4.406667 |
| 702 | 99 | 5.2 | 0.793333 | 4.406667 |
| 702 | 100 | 5.4 | 0.993333 | 4.406667 |
| 702 | 101 | 3.6 | -0.80667 | 4.406667 |
| 702 | 102 | 1.0 | -3.40667 | 4.406667 |
| 702 | 103 | 5.0 | 0.593333 | 4.406667 |
| 702 | 104 | 5.0 | 0.593333 | 4.406667 |
| 702 | 105 | 6.0 | 1.593333 | 4.406667 |
| 702 | 106 | 4.2 | -0.20667 | 4.406667 |
| 702 | 107 | 5.8 | 1.393333 | 4.406667 |
| 702 | 108 | 3.2 | -1.20667 | 4.406667 |
| 702 | 109 | 5.4 | 0.993333 | 4.406667 |
| 702 | 110 | 6.4 | 1.993333 | 4.406667 |
| 702 | 111 | 4.4 | -0.00667 | 4.406667 |
| 702 | 112 | 3.0 | -1.40667 | 4.406667 |
| 702 | 113 | 6.0 | 1.593333 | 4.406667 |
| 902 | 114 | 4.2 | 0.209524 | 3.990476 |
| 902 | 115 | 4.6 | 0.609524 | 3.990476 |
| 902 | 116 | 3.0 | -0.99048 | 3.990476 |
| 902 | 117 | 2.6 | -1.39048 | 3.990476 |
| 902 | 118 | 5.2 | 1.209524 | 3.990476 |
| 902 | 119 | 5.2 | 1.209524 | 3.990476 |
| 902 | 120 | 1.6 | -2.39048 | 3.990476 |
| 902 | 121 | 5.0 | 1.009524 | 3.990476 |
| 902 | 122 | 4.4 | 0.409524 | 3.990476 |
| 902 | 123 | 5.0 | 1.009524 | 3.990476 |
| 902 | 124 | 3.6 | -0.39048 | 3.990476 |
| 902 | 125 | 4.2 | 0.209524 | 3.990476 |
| 902 | 126 | 5.0 | 1.009524 | 3.990476 |
| 902 | 127 | 3.4 | -0.59048 | 3.990476 |
| 902 | 128 | 3.6 | -0.39048 | 3.990476 |
| 902 | 129 | 5.0 | 1.009524 | 3.990476 |
| 902 | 130 | 3.2 | -0.79048 | 3.990476 |
| 902 | 131 | 2.4 | -1.59048 | 3.990476 |
| 902 | 132 | 4.8 | 0.809524 | 3.990476 |
| 902 | 133 | 3.6 | -0.39048 | 3.990476 |
| 902 | 134 | 4.2 | 0.209524 | 3.990476 |
The scatterplot of the residuals versus the group variable is,
Interpretation: From the above graph, it is observed that the scatter plot of the residuals is symmetrically scattered below and above the zero and there are two outliers below the zero but these are not the extreme outliers.
(b)
To determine
Whether the spread of the residual of each group is relatively equal or not.
(b)
Expert Solution
Answer to Problem 22E
Solution: Yes, the spread of the residual of each group is relatively equal.
Explanation of Solution
From the scatterplot of the residuals versus the group variables in part (a), it is observed that the residuals are symmetrically scattered below and above the zero. It implies that the spread of the residual of each group is relatively equal.
(c)
To determine
To graph: The Normal quantile plot of the residuals obtained in part (a) and identify whether it is normal or not.
(c)
Expert Solution
Explanation of Solution
Graph:
Use Minitab to graph the Normal quantile plot as below:
Step1: Enter the provided data in the worksheet.
Step2: Select stat> ANOVA>one-way analysis of variance.
Step3: Select Score in the Response and Friends in the Factor.
Step4: Click on Graphs and select the Normal plot of residuals and then press OK.
Step5: Press OK.
The obtained graph is,
Interpretation: From the obtained graph, it is observed that the normal quantile plot is nearly fitted to the line. Hence, the residual is approximately normal.
Want to see more full solutions like this?
Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!
Students have asked these similar questions
The average miles per gallon for a sample of 40 cars of model SX last year was 32.1, with a population standard deviation of 3.8. A sample of 40 cars from this year’s model SX has an average of 35.2 mpg, with a population standard deviation of 5.4.
Find a 99 percent confidence interval for the difference in average mpg for this car brand (this year’s model minus last year’s).Find a 99 percent confidence interval for the difference in average mpg for last year’s model minus this year’s. What does the negative difference mean?
A special interest group reports a tiny margin of error (plus or minus 0.04 percent) for its online survey based on 50,000 responses. Is the margin of error legitimate? (Assume that the group’s math is correct.)
Suppose that 73 percent of a sample of 1,000 U.S. college students drive a used car as opposed to a new car or no car at all.
Find an 80 percent confidence interval for the percentage of all U.S. college students who drive a used car.What sample size would cut this margin of error in half?
Chapter 12 Solutions
Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
Ch. 12.1 - Prob. 1UYKCh. 12.1 - Prob. 2UYKCh. 12.1 - Prob. 3UYKCh. 12.1 - Prob. 5UYKCh. 12.1 - Prob. 6UYKCh. 12.1 - Prob. 4UYKCh. 12.2 - Prob. 7UYKCh. 12.2 - Prob. 8UYKCh. 12 - Prob. 9ECh. 12 - Prob. 10E
Ch. 12 - Prob. 11ECh. 12 - Prob. 12ECh. 12 - Prob. 13ECh. 12 - Prob. 14ECh. 12 - Prob. 15ECh. 12 - Prob. 16ECh. 12 - Prob. 17ECh. 12 - Prob. 18ECh. 12 - Prob. 39ECh. 12 - Prob. 19ECh. 12 - Prob. 43ECh. 12 - Prob. 41ECh. 12 - Prob. 42ECh. 12 - Prob. 49ECh. 12 - Prob. 20ECh. 12 - Prob. 21ECh. 12 - Prob. 28ECh. 12 - Prob. 29ECh. 12 - Prob. 30ECh. 12 - Prob. 35ECh. 12 - Prob. 36ECh. 12 - Prob. 23ECh. 12 - Prob. 24ECh. 12 - Prob. 25ECh. 12 - Prob. 26ECh. 12 - Prob. 31ECh. 12 - Prob. 32ECh. 12 - Prob. 33ECh. 12 - Prob. 34ECh. 12 - Prob. 37ECh. 12 - Prob. 38ECh. 12 - Prob. 27ECh. 12 - Prob. 40ECh. 12 - Prob. 45ECh. 12 - Prob. 46ECh. 12 - Prob. 47ECh. 12 - Prob. 48ECh. 12 - Prob. 50ECh. 12 - Prob. 51ECh. 12 - Prob. 52ECh. 12 - Prob. 53ECh. 12 - Prob. 54ECh. 12 - Prob. 55ECh. 12 - Prob. 56ECh. 12 - Prob. 57ECh. 12 - Prob. 58ECh. 12 - Prob. 59ECh. 12 - Prob. 60ECh. 12 - Prob. 63ECh. 12 - Prob. 22ECh. 12 - Prob. 67ECh. 12 - Prob. 68ECh. 12 - Prob. 69ECh. 12 - Prob. 44ECh. 12 - Prob. 61ECh. 12 - Prob. 62ECh. 12 - Prob. 64ECh. 12 - Prob. 65ECh. 12 - Prob. 66E
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- You want to compare the average number of tines on the antlers of male deer in two nearby metro parks. A sample of 30 deer from the first park shows an average of 5 tines with a population standard deviation of 3. A sample of 35 deer from the second park shows an average of 6 tines with a population standard deviation of 3.2. Find a 95 percent confidence interval for the difference in average number of tines for all male deer in the two metro parks (second park minus first park).Do the parks’ deer populations differ in average size of deer antlers?arrow_forwardSuppose that you want to increase the confidence level of a particular confidence interval from 80 percent to 95 percent without changing the width of the confidence interval. Can you do it?arrow_forwardA random sample of 1,117 U.S. college students finds that 729 go home at least once each term. Find a 98 percent confidence interval for the proportion of all U.S. college students who go home at least once each term.arrow_forward
- Suppose that you make two confidence intervals with the same data set — one with a 95 percent confidence level and the other with a 99.7 percent confidence level. Which interval is wider?Is a wide confidence interval a good thing?arrow_forwardIs it true that a 95 percent confidence interval means you’re 95 percent confident that the sample statistic is in the interval?arrow_forwardTines can range from 2 to upwards of 50 or more on a male deer. You want to estimate the average number of tines on the antlers of male deer in a nearby metro park. A sample of 30 deer has an average of 5 tines, with a population standard deviation of 3. Find a 95 percent confidence interval for the average number of tines for all male deer in this metro park.Find a 98 percent confidence interval for the average number of tines for all male deer in this metro park.arrow_forward
- Based on a sample of 100 participants, the average weight loss the first month under a new (competing) weight-loss plan is 11.4 pounds with a population standard deviation of 5.1 pounds. The average weight loss for the first month for 100 people on the old (standard) weight-loss plan is 12.8 pounds, with population standard deviation of 4.8 pounds. Find a 90 percent confidence interval for the difference in weight loss for the two plans( old minus new) Whats the margin of error for your calculated confidence interval?arrow_forwardA 95 percent confidence interval for the average miles per gallon for all cars of a certain type is 32.1, plus or minus 1.8. The interval is based on a sample of 40 randomly selected cars. What units represent the margin of error?Suppose that you want to decrease the margin of error, but you want to keep 95 percent confidence. What should you do?arrow_forward3. (i) Below is the R code for performing a X2 test on a 2×3 matrix of categorical variables called TestMatrix: chisq.test(Test Matrix) (a) Assuming we have a significant result for this procedure, provide the R code (including any required packages) for an appropriate post hoc test. (b) If we were to apply this technique to a 2 × 2 case, how would we adapt the code in order to perform the correct test? (ii) What procedure can we use if we want to test for association when we have ordinal variables? What code do we use in R to do this? What package does this command belong to? (iii) The following code contains the initial steps for a scenario where we are looking to investigate the relationship between age and whether someone owns a car by using frequencies. There are two issues with the code - please state these. Row3<-c(75,15) Row4<-c(50,-10) MortgageMatrix<-matrix(c(Row1, Row4), byrow=T, nrow=2, MortgageMatrix dimnames=list(c("Yes", "No"), c("40 or older","<40")))…arrow_forward
- Describe the situation in which Fisher’s exact test would be used?(ii) When do we use Yates’ continuity correction (with respect to contingencytables)?[2 Marks] 2. Investigate, checking the relevant assumptions, whether there is an associationbetween age group and home ownership based on the sample dataset for atown below:Home Owner: Yes NoUnder 40 39 12140 and over 181 59Calculate and evaluate the effect size.arrow_forwardNot use ai pleasearrow_forwardNeed help with the following statistic problems.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Big Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin Harcourt
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...AlgebraISBN:9781337111348Author:Bruce Crauder, Benny Evans, Alan NoellPublisher:Cengage Learning
Holt Mcdougal Larson Pre-algebra: Student Edition...AlgebraISBN:9780547587776Author:HOLT MCDOUGALPublisher:HOLT MCDOUGAL
College AlgebraAlgebraISBN:9781305115545Author:James Stewart, Lothar Redlin, Saleem WatsonPublisher:Cengage Learning
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Functions and Change: A Modeling Approach to Coll...
Algebra
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Cengage Learning
Holt Mcdougal Larson Pre-algebra: Student Edition...
Algebra
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY