28. Price Pol Po 0 C Price Po Pe'l 0 S D D' Price B Po Po- S 2.00 pts D' .D Qo Qo' Quantity 0 Qo' Qo Quantity D S Price S S Po Pe Qe Qo' Quantity 0 Qe' Qe Quantity Refer to the figure above. Which of the four graphs represents the market for movie theater tickets after a reduction in the price of home movie rentals? OA B D
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- 77. During a period of decline in stock market prices a stock sold at Rs. 50 per share on one day Rs. 40 on the next day and Rs. 25 on the third. (1) If an investor bought 100, 120 and 180 shares on the respective three days, find the average price paid per share. (ti) If the investor bought Rs. 1000 worth of shares on each of the three days, find the average price paid per share. IB.A. (H) Econ. Delhi Univ.. 2007: B.Com...c) If the price of the product is increased from 3.50 to 4.20 (a 20% increase): (1) Will the revenue from selling the products go up or down? UP/ DOWN (Circle one) (ii) Will the demand for the products go up or down? UP / DOWN (Circle one) By about what percentage?. _%6. In the table beloe provides predicted population data about the world and India.RegionPredicted Population (millions)Region: 2035 2050World : 8,933 9766India : 1,655.7 1670.1 (d) Calculate the absolute change in the percent of the world population that liives in India between 2035 and 2050. Round your results to one decimal place. (e) The predicted population of India is incresing while the percentage of the world population predicted to live is decresing. How can that happen? Explain in full sentences.
- 4. The following table provides the average price of Regular Grade of gasoline for 4 years. Use 2015 as the reference value, complete the table by calculating the price index for each year. Show all your calculation in the space provided. Date 2013 2014 2015 2016 Regular Grade Gasoline Prices Price $3.505 $3.358 $2.429 $2.143 Price IndexThe prices (in $) of Rawlston, Inc. stock ( y) over a period of 12 days, the number of shares (in 100s) of company's stocks sold ( x 1), and the volume of exchange (in millions) on the New York Stock Exchange ( x 2) are shown below. Day (y) (x1) (x2) 1 87.50 950 11.00 2 86.00 945 11.25 3 84.00 940 11.75 4 83.00 930 11.75 5 84.50 935 12.00 6 84.00 935 13.00 7 82.00 932 13.25 8 80.00 938 14.50 9 78.50 925 15.00 10 79.00 900 16.50 11 77.00 875 17.00 12 77.50 870 17.50 Excel was used to determine the least squares regression equation. Part of the computer output is shown below. ANOVA df SS MS F Significance F Regression 2 118.8474 59.4237 40.9216 0.0000 Residual 9 13.0692 1.4521 Total 11 131.9167 Coefficients Standard Error t Stat P-value Intercept…/23 . 24
- Use the following for questions 6-7: A random sample of 40 companies on the Forbes 500 list was selected and the relationship between sales (in hundreds of thousands of dollars) and profits (in hundreds of thousands of dollars) was investigated using regression. A least-squares regression line was fitted to the data using statistical software, with sales as the explanatory variable and profits as the response variable. Here is the output from the software: Dependent variable is Profits R-squared = 66.2% = 466.2 with 40 2 = 38 degrees of freedom Variable Constant Sales Coefficient -176.644 0.092498 s.e. of Coefficient 61.16 0.0106 P-value 0.0050 ≤0.00013. In the following example, a cohort of six individuals was followed for 100 days after an outbreak of a viral infection in a hospital ward. The graph below shows how many days each subject remained in the study as a non-case (not infected). Those who completed the study as non-cases reached 100 days - the rest fell ill and did become cases. Since we know person-time is used to determine the amount of time at risk, calculate the total time contributed by all six subjects in this study. Note for submission: please make sure to include your units and interpretation in your Worksheet so you have it for review for the midterm, even if Blackboard doesn't allow for this information to be included in your submitted answer! Calculating Person-days F 64 E 100 D. 100 37 55 12 20 40 60 80 100 Days20. A tennis player bounces a ball on her racket. This graph shows the height of the ball above the racket over time. Height (m) 1 0.8 0.6 0.4 0.2 14 Chor 0 0.4 0.6 Time (s) When is the ball moving the least rapidly? a. Around 0 s b. Around 0.9 s 0.2 0.8 1 nouston resuil a dobo tsonil isbon esiden noitele nonalar Yanortapps shom li sidst inozob Jesd insmelci. ESSI-S C. Around 0.45 s d. Around 0 s and 0.9 s i znojle
- b) Below are the no of customers, visiting a local Tesco Express, in the first week of holiday season. The store manager would like to avoid stock out in the busy period. Provide forecast of sales on Saturday next week, using 3 point moving average and seasonal variation. Assume same seasonal variation next period. 3 Point Moving Seasonal Week days Customers Average Variation Monday Tuesday Wednesday Thursday Friday Saturday Sunday (i) (ii) 1,525 1,352 1,250 1,400 1,515 1,815 1,750 Calculate daily trend, all rounded to units Calculate sales value trend in next turday, all rounded to units6. Which kind of relation models the data in this table? 1 4 y -17.1 4.6 -17.1 -82.2 -190.7 Linear b. Quadratic Exponential d. Constant a. с. 7. Express 72 x 76 as a single power. 72 b. 76 78 d. 712 a. 76 8. Express as a single power. 72 b. 74 c. 76 d. 73 a. 9. Evaluate 8 32 1024 59049 a. b. d. 27 243 10. Evaluate а. 0 b. c. 1 d. (-32) 3 11. Simplify (-33) а. 0 b. 1 c. 36 d. 3* 12. Simplify a. b. d. x4. A used car dealer wants to determine the relationship between the milage (in thousand miles) and the prices (in thousand dollars) of a certain model. He got the milage on 10 cars of this model and the resale prices of the cars. Cars 1 3 5 7 8 10 Milage 26.65 20.27 11.90 23.66 29.22 35.97 27.26 36.43 11.70 40.21 Prices 12.09 13.49 16.65 13.83 10.46 8.71 10.20 8.43 17.15 7.76 (a) If yes, find the linear regression line. Make a scatter plot of the data, does a straight line fit the data well? (b) Interpret the estimated slope 3, in part(a). (c) it. Use your regression line in part(a) to estimate the mean price she should Mary wants to buy a used car of this model with 20 thousand miles on expect. (d) miles. Can he use the regression line in part (a) to get the mean price? Explain. Jack is interested in another used car of this model with 5 thousand
