(7 Which of the following can cause OLS estimators to be biased? Heteroskedasticity. (ii) Omitting an important variable. (iii) A sample correlation coefficient of .95 between two independent variables both included in the model.
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- 1. Explain the meaning of: R-SQUARED F-TEST MULTICOLLINEARITY 2. Why are these considered as more important in multiple regression analysis? 3. How to detect problems in multicollinearity?A company has determined that there are seven possible defects for one of its product lines. Construct a Pareto diagram for the following defect frequencies:Defect Code FrequencyA 10B 70C 15D 90E 8F 4G 3Read the executive summary thoroughly and attempt the questions given below:The prevailing of fast food consumption and obesity in Iranian student is high. Fast food consumptionwas associate with abdominal obesity based on WHR, but did not has related to general obesity basedon BMI. In an analytical cross-sectional study, 300 students were selected random from the twolargest universities in Qom, center of Iran, studying in medical and basic sciences fields in 2015. Isuccessfully collected the data by a modified version of NELSON’S fast food questionnaire andanthropometric measures including Waist-Hip Ratio (WHR) and Body Mass Index (BMI). Chi-square,independent t-test, and multivariate logistic regression were used for statistical analysis. I want toestimate the prevalence of fast food consumption and to assess its association with abdominal andgeneral obesity. My results has shown that, 72.4% (67.4% in females vs 80.7% in males) had at leastone type of fast food consumption in the…
- A multiple regression analysis produced the following output from Minitab.Regression Analysis: Y versus x and xPredictor Coef SE Coef T PConstant -0.0626 0.2034 -0.31 0.762x 1.1003 0.5441 2.02 0.058x -0.8960 0.5548 -1.61 0.124S = 0.179449 R-Sq = 89.0% R-Sq(adj) = 87.8%Analysis of VarianceSource DF SS MS F PRegression 2 4.7013 2.3506 73.00 0.000ResidualError18 0.5796 0.0322Total 20 5.2809These results indicate that____________In exercise 1, the following estimated regression equation based on 10 observations was presented. y^=29.1270+.5906x1+.4980x2Here SST=6724.125, SSR=6216.375, sb1=.0813, and sb2=.0567. a) Compute MSR and MSE. b) Compute F and perform the appropriate F test. Use α=.05. c) Perform a t test for the significance of β1. Use α=.05. d) Perform a t test for the significance of β2. Use α=.05.Show that b ^β0 is an unbiased estimator of β0. (Hint: Use the fact that ^β1 isunbiased.
- What does the value for the coefficient mean in the regression analysis of both the company ? P-Values - how its related to customer satisfaction in the regression analysis of both the company ?You estimated a regression with the following output. Source | SS df MS Number of obs = 268 -------------+---------------------------------- F(1, 266) = 23.48 Model | 668419.175 1 668419.175 Prob > F = 0.0000 Residual | 7572666.51 266 28468.6711 R-squared = 0.0811 -------------+---------------------------------- Adj R-squared = 0.0777 Total | 8241085.68 267 30865.4895 Root MSE = 168.73 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 1.014128 .2092916 4.85 0.000 .6020489 1.426207 _cons | 9.173163 21.13463 0.43 0.665 -32.43929 50.78561…A car company wants to know the monthly sales made in ($000), based on the brand of vehicle. The data collected was entered on a MINITAB spreadsheet for analysis. Exhibit II below was subsequently generated. Exhibit 2 Model N Mean Median Tri.Mean Std Dev S.E. Mean Hyundai 23 109 135 107.64 * 1.34 Toyota 27 165 124 143.65 9.5 ** Determine the values of * and **. Give the unbiased point estimate for the average monthly earning from Hyundai Give the unbiased point estimate for the variance of monthly earning from Hyundai Assuming normality, construct and interpret a 90% confidence interval for the average monthly earning from Toyota You are required to test at the 5% level of significance the hypothesis that the average monthly earnings on Hyundai Vehicles is equal to $110,000 versus the alternative that it is different from $110,000.
- A regression of average weekly earnings (AWE, measured in dollars) on age(measured in years) using a random sample of college-educated full-timeworkers aged 25–65 yields the following: AWE = 696.7 + 9.6 X Age, R2 = 0.023, SER = 624.1.a. Explain what the coefficient values 696.7 and 9.6 mean.b. The standard error of the regression (SER) is 624.1. What are the unitsof measurement for the SER? (Dollars? Years? Or is SER unit-free?)c. The regression R2 is 0.023. What are the units of measurement for theR2? (Dollars? Years? Or is R2 unit-free?)d. What does the regression predict will be the earnings for a 25-year-oldworker? For a 45-year-old worker?e. Will the regression give reliable predictions for a 99-year-old worker?Why or why not?f. Given what you know about the distribution of earnings, do youthink it is plausible that the distribution of errors in the regressionis normal? (Hint: Do you think that the distribution is symmetric orskewed? What is the smallest value of earnings,…What is the lowest level of measurement for the data where the mode could bedetermined?A. NominalB. OrdinalC. IntervalD. Ratio Consider a data set of 11 distinct measurements with mean equal to A and median equalto B. If the highest value was decreased to a value smaller than the median B, how wouldthe mean and median be affected?A. The mean and median will both decrease.B. The mean and median will not change.C. The mean will not change and the median will decrease.D. The mean will decrease and the median will not change. What is one distinction between a parameter and a statistic?A. A parameter is only based on conceptual measurements, but a statistic is basedon a combination of real and conceptual measurements.B. A statistic changes every time you try to measure it (using different samples), but aparameter remains fixed.C. A parameter changes each time you try to measure it, but a statistic remains fixedacross samples.D. The true value of a statistic can never be known but the true…a simple linear regression equation shows the relationship between-