The data from data421.dat contains information on 78 seventh-grade students. We want to know how well each of IQ score and self-concept score predicts GPA using least-squares regression. We also want to know which of these explanatory variables predicts GPA better. Give numerical measures that answer these questions. (Round your answers to three decimal places.) find:(Regressor: IQ) R 2 find: (Regressor: Self-Concept) R 2 obs gpa iq gender concept 1 7.94 103 2 54 2 8.292 111 2 73 3 4.643 114 2 39 4 7.47 115 2 69 5 8.882 111 1 47 6 7.585 115 2 76 7 7.65 111 2 63 8 2.412 92 2 30 9 6 100 1 41 10 8.833 115 2 53 11 7.47 116 1 57 12 5.528 96 1 41 13 7.167 105 2 61 14 7.571 116 1 59 15 4.7 80 1 64 16 8.167 116 1 58 17 7.822 102 1 64 18 7.598 123 1 41 19 4 93 2 53 20 6.231 101 1 48 21 7.643 101 2 67 22 1.76 85 2 37 24 6.419 101 1 60 26 9.648 115 2 86 27 10.7 135 1 80 28 10.58 132 2 80 29 9.429 111 2 59 30 8 110 2 73 31 9.585 115 2 70 32 9.571 125 1 74 33 8.998 106 1 44 34 8.333 117 1 73 35 8.175 115 2 57 36 8 117 2 57 37 9.333 125 1 63 38 9.5 125 2 92 39 9.167 89 2 65 40 10.14 120 1 82 41 9.999 113 1 89 43 10.76 124 2 77 44 9.763 107 2 64 45 9.41 121 2 67 46 9.167 110 2 72 47 9.348 105 2 73 48 8.167 123 2 77 50 3.647 89 2 29 51 3.408 102 1 44 52 3.936 93 2 56 53 7.167 113 2 44 54 7.647 105 2 59 55 .53 104 2 53 56 6.173 91 2 41 57 7.295 113 2 59 58 7.295 109 1 53 59 8.938 99 1 54 60 7.882 120 1 76 61 8.353 139 2 70 62 5.062 89 2 56 63 8.175 119 2 55 64 8.235 130 2 67 65 7.588 121 2 45 68 7.647 119 2 59 69 5.237 101 1 67 71 7.825 109 2 67 72 7.333 95 1 48 74 9.167 110 2 56 76 7.996 110 2 66 77 8.714 123 1 26 78 7.833 108 1 70 79 4.885 112 2 36 80 7.998 124 1 46 83 3.82 86 2 78 84 5.936 102 1 76 85 9 108 1 68 86 9.5 100 1 72 87 6.057 93 2 76 88 6.057 110 1 43 89 6.938 100 2 54
(Regressor: IQ) R 2 = 0.3935(Regressor: Self-Concept) R 2 = 0.2771
The data from data421.dat contains information on 78 seventh-grade students. We want to know how well...
The data from data349.dat contains information on 78 seventh-grade students. We want to know how well each of IQ score and self-concept score predicts GPA using least-squares regression. We also want to know which of these explanatory variables predicts GPA better. Give numerical measures that answer these questions. (Round your answers to three decimal places.) (Regressor: IQ) R 2 (Regressor: Self-Concept) R 2 Which variable is the better predictor? IQ Self Concept obs gpa iq gender concept 1 7.94 112 ...
The data from data95.dat contains information on 78 seventh-grade students. We want to know how well each of IQ score and self-concept score predicts GPA using least-squares regression. We also want to know which of these explanatory variables predicts GPA better. Give numerical measures that answer these questions. (Round your answers to three decimal places.) (Regressor: IQ) R 2 : (Regressor: Self-Concept) R 2 : Which variable is the better predictor? IQSelf Concept obs gpa iq gender concept 1 7.94...
Make a graph of the distribution of IQ scores for the seventh-grade students in table 1.3. Describe the shape, center, and spread of the distribution as well as any outliers. IQ scores are usually said to be centered at 100. Is the midpoint for these students close to 100, clearly above, or clearly below? TABLE 1.3 Educational Data for 78 Seventh-Grade Self- OBS Gender concept 123 GPA 8.292 4.643 7.470 8.882 7.585 10.760 9.763 9.410 9.167 9.348 8.167 107 046...
1.40 Describe the IQ scores. Make a graph of the distribution of IQ scores for the seventh-grade students in Table 1.3. Describe the shape, center, and spread of the 26 Chapter 1 Looking at Data-Distributions TABLE 1.3 Educational Data for 78 Seventh-Grade Sltudents Educational Data for 78 Seventh-Grade Students OBS GPA 1O Gender concept I0 Genderconcept 7.940 8.292 4.643 7.470 8.882 7.585 7.650 2.412 6.000 10.760 9.763 003 9410 126 9.167 9.348 127 047 51 8.167 3.647 3.408 3.936 119...
Problem #1: Consider the below matrix A, which you can copy and paste directly into Matlab. The matrix contains 3 columns. The first column consists of Test #1 marks, the second column is Test # 2 marks, and the third column is final exam marks for a large linear algebra course. Each row represents a particular student.A = [36 45 75 81 59 73 77 73 73 65 72 78 65 55 83 73 57 78 84 31 60 83...
For determining half-lives of radioactive isotopes, it is important to know what the background radiation is in a given detector over a specific period. The following data were taken in a y -ray detection experiment over 98 ten-second intervals: 58 50 57 58 64 63 54 64 59 41 43 56 60 50 46 59 54 60 59 60 67 52 65 63 55 61 68 58 63 36 42 54 58 54 40 60 64 56 61 51 48...
1. Forecast demand for Year 4. a. Explain what technique you utilized to forecast your demand. b. Explain why you chose this technique over others. Year 3 Year 1 Year 2 Actual Actual Actual Forecast Forecast Forecast Demand Demand Demand Week 1 52 57 63 55 66 77 Week 2 49 58 68 69 75 65 Week 3 47 50 58 65 80 74 Week 4 60 53 58 55 78 67 57 Week 5 49 57 64 76 77...
Use the accompanying data set on the pulse rates (in beats per minute) of males to complete parts (a) and (b) below. LOADING... Click the icon to view the pulse rates of males. a. Find the mean and standard deviation, and verify that the pulse rates have a distribution that is roughly normal. The mean of the pulse rates is 71.871.8 beats per minute. (Round to one decimal place as needed.) The standard deviation of the pulse rates is 12.212.2...
Problem 8.4: Refer to Muscle Mass Problem 1.27. Second-order regression model (8.2) with independent normal error terms is expected to be appropriate. A. Fit regression model (8.2). Plot the fitted regression function and the data. Does the quadratic regression function appear to be a good fit here? Find R^2. B. Test whether or not there is regression relation; use α= .05. State the alternatives, decision rule and conclusion. C. Estimate the mean muscle mass for women aged 48...
Problem 4: Variables that may affect Grades The data set contains a random sample of STAT 250 Final Exam Scores out of 80 points. For each individual sampled, the time (in hours per week) that the student spent participating in a GMU club or sport and working for pay outside of GMU was recorded. Values of 0 indicate the students either does not participate in a club or sport or does not work a job for pay. The goal of...