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- Which of the following pairs quantities have a negative correlation? (A) Calorie- intake per day and weight (B) Time spent on studying MMW and final grade in MMW (C) Credit card purchases and savings per month (D) Electric consumption per month and Meralco billFind the value of mode from the data given below: Weight (kg) 2 113-1 17 Weight (kg.) No. of students No. of students 93-97 14 5 118-122 12 123-127 17 128-132 98-102 6. 103-107 108-112The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a = 0.01. Weight, x Variability in braking distance, y 5960 5320 6500 5100 5850 4800 D 1.72 1.93 1.88 1.61 1.66 1.50 E Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Họip = 0 H:p # 0 Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical value is O B. The critical values are – to = and to =
- Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. The variables used are: fare-avg price of a one-way fare, in dollars dist- distance of the flight, in miles .reg fare ldist. Source Model Residual 551.391705 Total lfare SS ldist _cons 875.094374 df The OLS results suggest that 1 323.702668 120024315 4,594 MS Coef. Std. Err. 4,595 190444913 Number of obs F(1, 4594) Prob > F R-squared Adj R-squared Root MSE t P>|t| .4025646 .0077517 51.93 0.000 2.399834 .0521601 46.01 0.000 4,596 2696.98 0.0000 0.3699 0.3698 .34645 [95% Conf. Intervall .3873676 .4177617 2.297575 2.502093 a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare. a 1% increase in distance is associated with approximately a .40% increase in the price of the fare. a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare. None of the above.For the data given below, fill in the blanks, using Formulas, Descriptive Statistics and Regression outputs. Mean of X2: 1) 28th Percentile of X1: 2) 3) Standard Deviation of X2: 4) Y XI X2 10 20 400 70 11 30 450 97 12 Median of X2: 10 350 54 5) Correlation Between X1 and Y: Minimum value of X2: 13 20 375 40 14 6) 30 400 65 15 9) bo : 25 400 94 16 7) b,. 30 450 53 17 8) 20 300 35 10) 11) 18 SSR: 10 300 75 19 SSE: 40 300 53 ST: F Statistics: 20 12) Regression output 20 350 64 13) 14) 21 30 450 68 22 Adjusted R Square: 10 400 96 23 15) MSE: 30 325 54 24 16) MSR: 25 17) Standard Error of Regression: 18) 19) 20) 26 Standard error of X2: 27 t-statistics of X2: 28 Fit the regression equation: 29 30 Sheet1Which of the following tools is not appropriate for studying the relationship between two numerica variables? Correlation coefficient Scatter plot Historam Regression
- Can you please check my workMlustration 12. From the following data compute the 3-yearly and 5-yearly moving averages and: Year : 1 3 4 7 8 9. 10 11 Values : 25 30 34 37 39 40 40 39 37 34 30llustration 21.14. Calculate the coefficient of contingency from the following data relating social status and intelligence: Social Status Dull Brilliant Average 35 Lower Middle Middle 22 23 38 70 32 Upper Middle 60 20 20
