The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperaturex1, the number of days in the month x), the averag purity x3, and the tons of product produced x4. The past year's historical data are available and are presented in the following table. 240 25 24 91 100 236 31 21 90 95 290 45 24 88 110 274 60 25 87 88 301 65 25 91 94 316 72 26 94 87 99 300 80 25 97
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.QUESTION 2 XXX Electric Illuminating Company is doing a survey on the relationship between electricity used in kilowatt-hours (thousand) and the number of rooms in a private single-family residence. A random sample of 10 homes was selected and the electricity consumption recorded as below. ii. Find a suitable linear regression equation ? = ? + ??. iii. Determine the number of kilowatt-hours (thousand) for an eleven-room residence.
- Question 4b. (b) Finally, the researcher is interested in examining the regression model for knowledge, attitudeand practices towards the COFLU-20. The following model was developed to forecastindividual practices towards COFLU-20 using knowledge and attitude scores.P = α + β K + δ Awhere P = Practice towards COFLU-20 scoreK = Knowledge towards COFLU-20 scoreA = Attitude towards COFLU-20 scoreThe data are processed using MINITAB and the output in Exhibit 1 below was obtained:Exhibit 1The regression equation is *************Predictor Coef SE t-ratio PConstant 4.755 0.462 10.282 0Knowledge 0.8 0.039 2.055 0.041Attitude 0.024 0.6 0.393 0.695R-sq = 81.5%Analysis of VarianceSOURCE DF SS MS F PRegression 2 38.06 19.03 2.284 0.104Error 297 2474.887 8.333Total 299 2512.947(i) Identify the dependent variable(s) and the independent variable(s).(ii) Is δ significant?Show proof of the testing process used to arrive at your decision.State what this means in terms of attitude and practices. (iii)…question 26 What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 8 women are shown in the table below. Time 54 88 82 61 39 40 84 83 Pounds 149 198 184 166 142 140 170 163 The equation of the linear regression line is: ˆyy^ = ?+ x (Please show your answers to 3 decimal places) Use the model to predict the weight of a woman who spends 50 minutes on the phone.Weight = ? (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: For every additional minute women spend on the phone, they tend to weigh on averge 0.87 additional pounds. As x goes up, y goes up. The slope has no practical meaning since you cannot predict a women's weight. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. The average woman's weight is…Question 16 Regression analysis was applied between sales (in $1000s) and advertising (in $100s), and the following regression function was obtained. = 500 + 4x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is _____. $505,000 $900 $40,500 $900,000
- Question 9 Assume a regression analysis yields a regression line with the value Y=$120,000 + $0.58X, where Y equals plant labor costs and X equals dollars of production output. If the company plans to produce $2,400,000 of product during the upcoming month, it would project plant labor costs to be: a. $324,000 b. $120,000 c. $204,000 d. $2,400,000Question 4 The following table shows information related to the number of salesman and sales made in October 2020 for Jubilee Berhad: Salesman Sales 1 200 2 260 3 700 4 840 5 1,000 6 1,100 Required: Forecast the total sales if the company has 10 salesman. Determine the correlation coefficient between the number of salesman and total sales if the company maintain the existing number of salesman. The sales trend can be described by the linear regression equation y = 780 + 4x, where x is the month number (with January 2013 as month 0) and y is sales in RM'000. The average seasonal variation for March is 106%. Forecast the sales for March 2015 (in thousand RM). Badrol anticipates that a 90% learning curve will apply to the production of a new item. The first item will cost RM2,500.00 in materials, and will take 500 labour hours. The cost per hour for labour and variable overhead is RM15.00. Calculate the total cost…Problem 2 The following printout shows the results of a simple linear regression model that predicts monthly sales (in thousands of dollars) based on how much money was spent on advertising (in thousands of dollars) during a particular month for 15 stores of a retail chain. a) Is there a statistically significant relationship between money spent on advertising and sales? Test at the 5% level of significance and explain your approach (including hypotheses). b) Somebody claims that every additional $1,000 in advertising will increase sales by more than $2,000 in the population. Can you find support for this claim given the results of your analysis? Test at the 5% level of significance and explain your approach (including hypotheses). How is this test different from the one in part a)? c) Find a 95% confidence interval for the change in sales given a $1,000 increase in the amount of money spent on advertising. How does this confidence interval relate to your answer to part a)?
- Question 4 The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. Fit the regression line y = a+bx to the data and interpret the results. Use the regression equation to determine the SY16C grade for a college student who scored 60 on their achievement test. What would their SY16C grade be? Mathematics test (x) SY16C grades (y) 1 39 65 2 43 78 3 21 52 4 64 82 5 57 92 6 47 89 7 28 73 8 75 98 9 34 56Question 3. Calculate and interpret the regression line for the data.Question 5 - what is the y-intercept of the equation of the regression line y = 36.11695 + 7.20508x A. 7.20508 B. 36.11695 C. Y D. X Question 6 - what is the slop of the equation of the regression line y = 36.11695 + 7.20508x? A. 7.20508 B. 36.11695 C . Y D . X