Use the Table given below to find out: a. Correlation coefficient between Hydrocarbon levels and purity. b. Regression model.
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![Question-6
Use the Table given below to find out:
a. Correlation coefficient between Hydrocarbon levels and purity.
b. Regression model.
Observation
number
1
2
3
4
5
6
7
8
9
10
11/
12
Hydrocarbon
Levels, %
0.99
1.02
1.15
1.29
1.46
1.36
0.87
1.23
1.55
1.4
1.19
1.15
Purity
%
90.01
89.05
91.43
93.74
96.73
94.45
87.59
91.77
99.42
93.65
93.54
92.52
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- Part A: What is the most likely value of the correlation coefficient of the data in the table? Based on the correlation coefficient, describe the relationship between time and surface area of the lake. [Choose the value of the correlation coefficient from −1, −0.98, −0.5, −0.02.] Part B: What is the value of the slope of the graph of surface area versus time between 15 and 20 days, and what does the slope represent? Part C: Does the data in the table represent correlation or causation? Explain your answer.The correlation between agarwood formation size and the injection volume of fungal spores was statistically significant (p < 0.05). The regressed equation is y = 10.2 – 2.3x and the coefficient of determination (R2) is 0.76. What is the correlation coefficient (r) value for this relationship? a. r = – 0.76 b. r = 0.76 c. r = – 0.87 d. r = 0.87Match 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=0.810 (a) Scatter diagram (b) Scatter diagram (c) Scatter diagram Response Response Response = Explanatory Explanatory Explanatory
- estion 3 of 38 university and gathers their freshman year GPA data and the high school SAI score reported on each of their college applications. He produces a scatterplot with SAT scores on the horizontal axis and GPA on the vertical axis. The data has a linear correlation coefficient of 0.506701. Additional sample statistics are summarized in the table below. Variable Sample Sample standard Variable description mean deviation high school SAT score x 1504.291401 Sx = 105.782904 %3D y freshman year GPA y = 3.240805 Sy = 0.441205 r = 0.506701 slope 0.002113 Determine the y-intercept, a, of the least-squares regression line for this data. Give your answer precise to at least four decimal places. tems of use Thelp about us குசங் careers 2:30 PM 10/24/20 o耳 国 @ hpReport the correlations between the three independent variables (age, educ and Protestant) and your dependent variable (childs). Which category had the correlation that was the weakest?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= 0.946, (b) r= 0.523, (c) r = 1 (a) Scatter diagram (b) Scatter diagram Explanatory (c) Scatter diagram ........ Explanatory Explanatory Click to select your answer(s) and then click Check Answer. All parts showing Clear All e Type here to search DELL
- For the data below, the Pearson correlation coefficient between y and x^2 isA. 0.913B. 0.985C. 0.990D. 0.873A regression model is desired relating temperature and the proportion of impurities passing through solid helium. Temperature is listed in degrees centigrade. The data are as follows: Temperature (°C) -260.5 -255.7 -264.6 -265.0 -270.0 -272.0 -272.5 -272.6 -272.8 -272.9 Proportion of Impurities 0.425 0.224 0.453 0.475 0.705 0.860 0.935 0.961 0.979 0.990 (a) Fit a linear regression model. (b) Does it appear that the proportion of impurities passing through helium increases as the temperature approaches -273 degrees centigrade? (c) Find R². (d) Based on the information above, does the linear model seem appropriate? What additional information would you need to better answer that question?indicator for gender (=1 if male, =0 if female). Your data set has 200 observations. donation = 1.57 + 0.12age + 0.08age? – 0.43 gender + 0.07(gender * age), R? = 0.33 (0.15)* (0.67) (0.11) (0.01) (0.06) donation = 1.59 (0.68) 0.46 gender, R² = 0.30 (0.17) 1. Assuming homoscedastic errors, test the hypothesis that age affects charitable donations at the 5% level. 2. Interpret the coefficient on gender interacted with age. 3. How would you test that the difference in giving between men and women is independent of age? If you can run the test, run it. If you cannot, explain what you need.
- The scatter plot for a set of X and Y values shows the data points clustered in a nearly perfect circle. For these data, what is the most likely value for the Pearson correlation? A value near+1.00 or -1.00 Either positive or negative near O A negative correlation near O A positive correlation near OIn the simple linear regression Y = 20 - 5X, if the coefficient of determination is 0.8, then the sample correlation coefficient is Select one: O a. 0.89 Ob. 0.64 OC. -0.89 Od. -0.64 Next pageTable 1: Bivariate Correlations for the following variables: income, number of siblings, education, age, white, black and gender (1)rincome 1.00 (2)sibs (3)edu (4)age (5)white (6)black (1) (8)male Mean -0.06 0.30 0.16 0.12 (7)female -0.21 -0.12 0.21 13.91 Standard Dev. 5.63 (2) 1.00 -0.21 0.09 -0.27 0.27 0.02 -0.02 3.505 2.927 (3) 1.00 0.05 0.12 -0.12 0.02 -0.02 13.39 2.93 (4) 1.00 0.12 -0.12 0.03 47.12 (5) -0.03 -0.07 17.50 1.00 -1.00 0.07 .84 .37 (6) 1.00 .07 -.07 .16 .37 (7) 1.00 -1.00 i. There is a negative correlation between family size and income. ii. Income is positively correlated with education. iii. Income is positively correlated with age. iv. Income is positively correlated with white race. v. The black race is negatively correlated with income. vi. Income is negatively correlated with females. vii. Income is positively correlated with males. .56 .50 (8) 1.00 .44 .50 Note: rincome is respondent's income, sibs is respondent's number of siblings, age represents respondent's…
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