MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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(c) Does the data collected indicate that the monthly sales of a store can be expressed as a linear function the percentage of high school graduates in its customer base? Select the correct statisticaly hypotheses. А. Но : В1 В. Но : В — о На : В >0 C. Ho : B1 20 HẠ : B1 > 0 D. Ho : B1 = 0 HẠ : B1 + 0 E. Ho : B1 2 0 HẠ: B1 < 0 F. Ho : B1 > 0 HẠ : B1 0 HA : B1 < 0 (d) Using the F-test, test the statistical hypotheses determined in (c). Find the value of the test statistic, using two decimals in your answer. Feale %3D (e) Testing the statistical hypotheses in (c) at a = 0.05, you can conclude from this data that the ? ? v be expressed as a linear function of the ? (f) Can you infer from this data that an increase of 1% to the percentage of high school graduates in the customer based will lead to an mean/average increase in the store's monthly sales by more than $50,000? (i) Find the value of the test statistic, use two decimal places in your answer. Tcalc ... (ii) Find the P-value of the result, using three decimals. P-value = (g) A store located at a local mall has recently discovered that 90% of its customer base has a high school diploma. With 95% confidence, estimate this store's monthly sales for the current month. 38 38 Note: You will need E, Percent HSGrads; = 2935.17 and E, Percent H SGrads = 228777 i=1 i=1 Lower Bound = $1000s (use one decimal in your answer) Upper Bound = $1000s (use one decimal in your answer) (h) A residual plot of the regression was consulted. Residual Plot (Response is Sales in $1000s) 2000 1500 1000 - 500 - -500 - -1000 -1500 500 1000 1500 2000 2500 Fitted Value O O Residual
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Transcribed Image Text:(c) Does the data collected indicate that the monthly sales of a store can be expressed as a linear function the percentage of high school graduates in its customer base? Select the correct statisticaly hypotheses. А. Но : В1 В. Но : В — о На : В >0 C. Ho : B1 20 HẠ : B1 > 0 D. Ho : B1 = 0 HẠ : B1 + 0 E. Ho : B1 2 0 HẠ: B1 < 0 F. Ho : B1 > 0 HẠ : B1 0 HA : B1 < 0 (d) Using the F-test, test the statistical hypotheses determined in (c). Find the value of the test statistic, using two decimals in your answer. Feale %3D (e) Testing the statistical hypotheses in (c) at a = 0.05, you can conclude from this data that the ? ? v be expressed as a linear function of the ? (f) Can you infer from this data that an increase of 1% to the percentage of high school graduates in the customer based will lead to an mean/average increase in the store's monthly sales by more than $50,000? (i) Find the value of the test statistic, use two decimal places in your answer. Tcalc ... (ii) Find the P-value of the result, using three decimals. P-value = (g) A store located at a local mall has recently discovered that 90% of its customer base has a high school diploma. With 95% confidence, estimate this store's monthly sales for the current month. 38 38 Note: You will need E, Percent HSGrads; = 2935.17 and E, Percent H SGrads = 228777 i=1 i=1 Lower Bound = $1000s (use one decimal in your answer) Upper Bound = $1000s (use one decimal in your answer) (h) A residual plot of the regression was consulted. Residual Plot (Response is Sales in $1000s) 2000 1500 1000 - 500 - -500 - -1000 -1500 500 1000 1500 2000 2500 Fitted Value O O Residual
A national sporting good store wishes to use demographic information to predict its monthly sales, in $1000s. Thrity-eight, n = 38, stores of the chain are randomly chosen across the country. It is known that each store is approximately the same size and carries the same merchandise. The geographic area from which a store draws its customers is known as the customer base. One of the variables is the percentage of the customer base who have graduated from high school. MonthlySales; = Bo + Bị Percent H SGrads; + e; where MonthlySales; - is the total sales in month i, in $1000s Percent H SGrads; - is percentage of all customers in store i customer base that have graduated from high school A least-squares regression was ran in R producing the following output: Scatter Plot: Sales to High School Graduates 4000 - 3500 3000 - 2500 - 2000 1500- 1000 - 500 - 0- 50 55 60 65 70 75 80 85 90 95 Percentage of Customer Base with a HS Diploma Regression Analysis: MonthlySales versus PercentHSGrads Predictor Coef SD Coef TP Constant |-2970 1371 PercentHSGrads 59.66 17.67 S = 802.004 R-Sq = %3D Analysis of Variance Source DF S MS FP Regression 7333350 Residual Error 23155564 Total 37 Using the partial R output, answer the questions below. (a) Estimate the model. Use two-decimals your estimation of the slope term, no decimals in the estimation of the y-intercept. MonthlySales; : Percent H SGrads; + (b) What percentage of the variation in a store's monthly sales cannot be explained by its linear dependency on the percentage of the customer base that are high school graduates? Enter your answer as a percentage, using two decimal places. % Sales in $1000s
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Transcribed Image Text:A national sporting good store wishes to use demographic information to predict its monthly sales, in $1000s. Thrity-eight, n = 38, stores of the chain are randomly chosen across the country. It is known that each store is approximately the same size and carries the same merchandise. The geographic area from which a store draws its customers is known as the customer base. One of the variables is the percentage of the customer base who have graduated from high school. MonthlySales; = Bo + Bị Percent H SGrads; + e; where MonthlySales; - is the total sales in month i, in $1000s Percent H SGrads; - is percentage of all customers in store i customer base that have graduated from high school A least-squares regression was ran in R producing the following output: Scatter Plot: Sales to High School Graduates 4000 - 3500 3000 - 2500 - 2000 1500- 1000 - 500 - 0- 50 55 60 65 70 75 80 85 90 95 Percentage of Customer Base with a HS Diploma Regression Analysis: MonthlySales versus PercentHSGrads Predictor Coef SD Coef TP Constant |-2970 1371 PercentHSGrads 59.66 17.67 S = 802.004 R-Sq = %3D Analysis of Variance Source DF S MS FP Regression 7333350 Residual Error 23155564 Total 37 Using the partial R output, answer the questions below. (a) Estimate the model. Use two-decimals your estimation of the slope term, no decimals in the estimation of the y-intercept. MonthlySales; : Percent H SGrads; + (b) What percentage of the variation in a store's monthly sales cannot be explained by its linear dependency on the percentage of the customer base that are high school graduates? Enter your answer as a percentage, using two decimal places. % Sales in $1000s
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