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Q: To inspect incoming shipments of components, a manufacturer is considering samples of sizes 12, 15, and 18. Use binomial probabilities to select a sampling plan that provides a producer's risk of = .12 when p0is .04 and a consumer's risk of = .08 when p1is .25.

Q: A U.S. manufacturer of video cassette recorders purchases a circuit board from a Taiwanese firm. The circuit boards are shipped in lots of 2000. The acceptance sampling procedure uses 12 randomly selected circuit boards. The acceptance number is 1. If p0is .03 and p1is .20, what are the producer's and consumer's risks for this plan?

Q: Snipper, Inc. manufactures lawnmowers that require minor, final assembly bythe customer. A sealed plastic bag containing the hardware (nuts, bolts, washers, and so on) needed for final assembly is included with each lawnmower shipped.During a week of normal, in-control operation, twenty samples of 200 bags of hardware were examined for content (hardware type and count) accuracy. A total of 104 bags of the 4000 examined failed to have the correct contents.a. Compute the upper limit, center line, and lower limit for a pchart.b. Compute the upper limit, center line, and lower limit for an npchart.

Q: The weight of bags of cement filled by Granite Rock Company's packaging process is normally distributed with a mean of 50 pounds and a standard deviation of 1.5 pounds when the process is in control. What should the control limits be for a sample mean, , chart if 9 bags are sampled at a time?

Q: The quality control department of a company has decided to select a sample of 10 items from the shipments received; and if the sample contains no defective parts, the entire shipment will be accepted.a. If there are 40 defective items in a shipment, what is the probability that the entire lot will be accepted?b. Use the binomial table and read the probability of accepting lots that contain 5, 10, 15, 20, 25, 30, 35, 40, 45, and 50% defective units.

Q: An acceptance sampling plan uses a sample of 18 with an acceptance criterion of zero. Determine the probability of accepting shipments that contain 5, 10, 15, 20, 25, 30, 35, 40, and 45% defective units.

Q: The quality control department of a company has decided to select a sample of 20 items from each shipment of goods it receives and inspect them for defects. It has been decided that if the sample contains no defective parts, the entire lot will be accepted. Each shipment contains 1,000 items.a. What is the probability of accepting a lot that contains 10% defective items?b. What is the probability of accepting a lot that contains 5% defective items?c. What is the probability of rejecting a lot that contains 15% defective items?

Q: Brakes Shop, Inc., is a franchise that specializes in repairing brake systems of automobiles. The company purchases brake shoes from a national supplier. Currently, lots of 1,000 brake shoes are purchased, and each shoe is inspected before being installed on an automobile. The company has decided, instead of 100% inspection, to adopt an acceptance sampling plan.a. Explain what is meant by the acceptance sampling plan.b. If the company decides to adopt an acceptance sampling plan, what kinds of risks are there?c. The quality control department of the company has decided to select a sample of 10 shoes and inspect them for defects. Furthermore, it has been decided that if the sample contains no defective parts, the entire lot will be accepted. If there are 50 defective shoes in a shipment, what is the probability that the entire lot will be accepted?d. What is the probability of accepting the lot if there are 100 defective units in the lot?

Q: A production process is considered in control if 4% of the items produced are defective. Samples of size 100 are used for the inspection process.a. Determine the standard error of the proportion.b. Determine the upper and the lower control limits for the pchart.

Q: A production process is considered in control if 6% of the items produced are defective. Samples of size 300 are used for the inspection process.a. Determine the standard error of the proportion.b. Determine the upper and the lower control limits for the pchart.

Q: The following data represent the filling weights based on samples of 350-gram containers. Ten samples of size 5 were taken. Use Excel to develop an x-bar chart.SampleObserv. 1Observ. 2Observ. 3Observ. 4Observ. 51333.6226339.3906361.9761339.1192346.45782365.5820347.4967349.5748352.6524363.70963363.8708367.4003335.0422328.8487355.85094338.4916338.6541346.3491366.9538343.17675355.2305345.7635356.5218347.2718334.54346345.6990326.0756328.9903362.4881352.87187334.7083359.4960333.1609352.2697360.82568341.2400356.8819369.7263336.0729361.55629356.7090343.1499373.2071352.1363353.294910351.4613338.4823366.3254346.1882343.1589

Q: The following data represent the filling weights based on samples of 350-gram containers. Ten samples of size 5 were taken. Use Excel to develop an Rchart.SampleObserv. 1Observ. 2Observ. 3Observ. 4Observ. 51333.6226339.3906361.9761339.1192346.45782365.5820347.4967349.5748352.6524363.70963363.8708367.4003335.0422328.8487355.85094338.4916338.6541346.3491366.9538343.17675355.2305345.7635356.5218347.2718334.54346345.6990326.0756328.9903362.4881352.87187334.7083359.4960333.1609352.2697360.82568341.2400356.8819369.7263336.0729361.55629356.7090343.1499373.2071352.1363353.294910351.4613338.4823366.3254346.1882343.1589

Q: The following data represent the filling weights based on samples of 14.5 ounce cans of whole peeled tomatoes. Ten samples of size 5 were taken. Use Excel to develop an x-bar chart.SampleObserv. 1Observ. 2Observ. 3Observ. 4Observ. 5114.3498813.8611614.6221315.1382415.09918214.1549013.6547813.5765414.0111914.11325314.3365014.3148815.1713214.4573614.40692415.3307313.6938014.7694714.9511015.45946513.7779114.0763813.7392114.3185614.48376613.2112115.2238413.8601214.1732114.87886714.8470014.6613214.0300814.3795314.56577814.5361214.9149214.9310014.1817314.03840915.6028415.2218815.1519514.5564814.500981014.7221114.8089514.6067413.9865315.11910

Q: The following data represent the filling weights based on samples of 14.5 ounce cans of whole peeled tomatoes. Ten samples of size 5 were taken. Use Excel to develop an Rchart.SampleObserv. 1Observ. 2Observ. 3Observ. 4Observ. 5114.3498813.8611614.6221315.1382415.09918214.1549013.6547813.5765414.0111914.11325314.3365014.3148815.1713214.4573614.40692415.3307313.6938014.7694714.9511015.45946513.7779114.0763813.7392114.3185614.48376613.2112115.2238413.8601214.1732114.87886714.8470014.6613214.0300814.3795314.56577814.5361214.9149214.9310014.1817314.03840915.6028415.2218815.1519514.5564814.500981014.7221114.8089514.6067413.9865315.11910

Q: The upper and lower control limits of a process are 66 and 54. Samples of size 16 are used for the inspection process. Determine the mean and the standard deviation for this process.

Q: A production process that is in control has a mean () of 80 and a standard deviation () of 10.a. Determine the upper and the lower control limits for sample sizes of 25.b. Five samples had means of 81, 84, 75, 83, and 79. Construct an x-bar chart and explain whether or not the process is in control.

Q: A soft drink filling machine is set up to fill bottles with 12 ounces of soft drink. The standard deviation sis known to be 0.4 ounces. The quality control department periodically selects samples of 16 bottles and measures their contents. Assume the distribution of filling volumes is normal.a. Determine the upper and lower control limits and explain what they indicate.b. The means of six samples were 11.8, 12.2, 11.9, 11.9, 12.1, and 11.8 ounces. Construct an x-bar chart and indicate whether or not the process is in control.

Q: The two general classifications of attributes in quality control area. random and predictableb. controllable and uncontrollablec. variable and constantd. defective and nondefective

Q: If the value of c in a single-stage sampling plan is increased, with n remaining constant, the probability of accepting the lot a. increases b. decreases c. is unchanged d. might increase or decrease, depending on the lot percent defective

Q: The second stage of a two-stage acceptance sampling plan is executed when the first-stage result is a. x1> c1 b. c1< x1< c2 c. x1> c2 d. x1>c1+ c2

Q: DFSS stands for a. Defects Found Sifting and Sorting b. Design For Six Sigma c. Deviation From Standards or Specifications d. Defer For Statistical Study

Q: Six Sigma represents a quality level of at most ____ defects per million opportunities. a. 3.4 b. 6.0 c. 19.7 d. 99.5

Q: When a Motorola executive said "That evaluation is "¦. perhaps the most cost-effective, value-added business consultation available anywhere in the world today" he was referring to a. ISO 9000 standards b. the Six Sigma philosophy c. Deming's 14 Points d. the Malcolm Baldrige Quality Award

Q: The Malcolm Baldrige National Quality Award was established in a. 1954 b. 1971 c. 1987 d. 1993

Q: In contrast to Deming's philosophy, which required a major cultural change in the organization, Juran's programs were designed to improve quality by a. working within the current organizational system b. reducing the number of levels in the organizational structure c. changing customer perception and expectations d. identifying and replacing the most counter-productive employees

Q: The three quality processes on which Juran's approach to quality focused include all of the following except a. quality planning b. quality execution c. quality control d. quality improvement

Q: Juran proposed a simple definition of quality: a. customer satisfaction b. conformance to specifications c. fitness for use d. commitment to excellence

Q: A form of acceptance sampling in which more than one sample or stage is used is called a a. single-sample plan b. multiple-sampling plan c. multinomial sampling plan d. None of the other answers is correct.

Q: The maximum number of defective items that can be found in the sample and still lead to acceptance of the lot is a. the upper control limit b. the lower control limit c. the acceptance criterion d. None of the other answers is correct.

Q: A graph showing the probability of accepting the lot as a function of the percent defective in the lot is a. a power curve b. a control chart c. an operating characteristic curve d. None of the other answers is correct.

Q: Rejecting a poor-quality lot would be a a. Type I error b. Type II error c. correct decision d. None of the other answers is correct.

Q: Accepting a good-quality lot would be a a. Type I error b. Type II error c. correct decision d. None of the other answers is correct.

Q: Consumer's risk is a. the same concept as the producer's risk b. a Type II error c. a Type I error d. None of the other answers is correct.

Q: In acceptance sampling, the risk of accepting a poor quality lot is known as a. consumer's risk b. producer's risk c. a Type I error d. None of the other answers is correct.

Q: Producer's risk is a. the same as the consumer's risk b. a Type II error c. a Type I error d. None of the other answers is correct.

Q: In acceptance sampling, the risk of rejecting a good quality lot is known as a. consumer's risk b. producer's risk c. a Type II error d. None of the other answers is correct

Q: A statistical procedure in which the number of defective items found in a sample is used to determine whether a lot should be accepted or rejected is called a. statistical process control b. acceptance sampling c. quality assurance d. control charts

Q: A group of items such as incoming shipments of raw material is called a. a sample plan b. an incoming control c. a lot d. None of the other answers is correct.

Q: The control limits for an npchart are how many standard deviations above and below the expected number of defectives? a. one b. two c. three d. four

Q: A control chart that is used to monitor the number of defectives in a sample is a. a pchart b. an x-bar chart c. an Rchart d. an npchart

Q: A control chart that is used to monitor the range of the measurements in a sample is a. a pchart b. an x-bar chart c. an Rchart d. an npchart

Q: The control limits for a pchart are how many standard deviations above and below the proportion defective? a. one b. two c. three d. four

Q: If the calculated lower-control limit of a pchart is negative, a. a mistake has been made in the calculations b. use the absolute value of the lower limit c. it is set to zero d. None of the other answers is correct.

Q: A control chart that is used when the output of a production process is measured in terms of the proportion defective is a. a pchart b. an x-bar chart c. an Rchart d. an npchart

Q: The control limits for an x-bar chart are how many standard deviations above and below the process mean? a. one b. two c. three d. four

Q: A control chart used when the output of a process is measured in terms of the mean value of a variable such as a length, weight, temperature, and so on is a. a pchart b. an x-bar chart c. an Rchart d. an npchart

Q: Which of the following is not a type of a control chart? a. a pchart b. an x-bar chart c. an Rchart d. All of these are types of control charts.

Q: A graphical tool used to help determine whether a process is in control or out of control is a a. scatter diagram b. histogram c. control chart d. None of the other answers is correct.

Q: Normal or natural variations in the quality of production output that are due purely to chance are a. common causes b. assignable causes c. control causes d. None of the other answers is correct.

Q: Variations in the quality of production output that are due to factors such as machine tools wearing out are a. common causes b. assignable causes c. control causes d. None of the other answers is correct.

Q: Which of the following is a statistical method used in quality control? a. statistical process control b. acceptance sampling c. Both statistical process control and acceptance sampling are correct. d. None of the other answers is correct.

Q: __________ consist(s) of making a series of inspections and measurements to determine whether quality standards are being met. a. Quality control b. Quality engineering c. Quality assurance d. Both quality control and quality engineering are correct.

Q: Quality assurance consists of a. quality control b. quality engineering c. quality assurance d. Both quality control and quality engineering are correct.

Q: The entire system of policies, procedures, and guidelines established by an organization to achieve and maintain quality is called a. quality control b. quality engineering c. quality assurance d. Both quality control and quality engineering are correct.

Q: The sample result plotted on an npcontrol chart is a. np b. np c. the number of perfect units in the sample d. the number of defective units in the sample

Q: The general practice in quality control is to set the control chart's upper and lower control limit values equal to the variable's mean value +/ a. 1 standard deviation b. 2 standard deviations c. 2.5 standard deviations d. 3 standard deviations

Q: If the value of cin a single-stage acceptance sampling plan is increased, with nremaining constant, the probability of accepting the lot a. increases b. decreases c. remains the same d. might increase or decrease, depending on the percent defective in the lot

Q: An operating characteristic curve is based on a ________ probability distribution. a. normal b. exponential c. binomial d. uniform

Q: Control charts that are based on data indicating the presence of a defect or the number of defects are called ______ control charts. a. attributes b. variables c. common-cause d. assignable-cause

Q: A company has recorded data on the weekly sales for its product (y), the unit price of the competitor's product (x1), and advertising expenditures (x2). The data resulting from a random sample of 7 weeks follows. Use Excel's Regression Tool to answer the following questions.WeekPriceAdvertisingSales1.335202.252143.447224.409215.354166.398197.29915a. What is the estimated regression equation?b. Determine whether the model is significant overall. Use = 0.10.c. Determine if price is significantly related to sales. Use = 0.10.d. Determine if advertising is significantly related to sales. Use = 0.10.e. Find and interpret the multiple coefficient of determination.

Q: The following regression model has been proposed to predict monthly sales at a shoe store. = 40 " 3x1+ 12x2+ 10x3wherex1= competitor's previous month's sales (in $1,000s)x2= Stores previous month's sales (in $1,000s) = sales (in $1000s)a. Predict sales (in dollars) for the shoe store if the competitor's previous month's sales were $9,000, the store's previous month's sales were $30,000, and no radio advertisements were run.b. Predict sales (in dollars) for the shoe store if the competitor's previous month's sales were $9,000, the store's previous month's sales were $30,000, and 10 radio advertisements were run.

Q: The following regression model has been proposed to predict sales at a computer store. = 50 " 3x1+ 20x2+ 10x3 where x1= competitor's previous day's sales (in $1,000s) x2= population within 1 mile (in 1,000s) = sales (in $1000s) Predict sales (in dollars) for a store with the competitor's previous day's sale of $5,000, a population of 20,000 within 1 mile, and nine radio advertisements.

Q: The following regression model has been proposed to predict sales at a fast food outlet. = 18 " 2x1+ 7x2+ 15x3wherex1= the number of competitors within 1 milex2= the population within 1 mile (in 1,000s)x3= 1 if drive-up windows are present, 0 otherwise = sales (in $1,000s)a. What is the interpretation of 15 (the coefficient of x3) in the regression equation?b. Predict sales for a store with 2 competitors, a population of 10,000 within one mile, and one drive-up window (give the answer in dollars).c. Predict sales for the store with 2 competitors, a population of 10,000 within one mile, and no drive-up window (give the answer in dollars).

Q: A sample of 25 families was taken. The objective of the study was to estimate the factors that determine the monthly expenditure on food for families. The independent variables included in the analysis were the number of members in the family (x1), the number of meals eaten outside the home (x2), and a dummy variable (x3) that equals 1 if a family member is on a diet and equals 0 if there is no family member on a diet. The following results were obtained.ANOVAdfSSMSFRegression3,078.391,026.13Error2,013.9095.90CoefficientsStandard ErrorIntercept150.0853.6x149.929.6x210.122.2x3-.6012.0a. Write out the estimated regression equation.b. Interpret all coefficients.c. Compute the appropriate tratios.d. Test for the significance of 1, 2, and 3at the 1% level of significance.e. What are the degrees of freedom for the sum of squares explained by the regression (SSR) and the sum of squares due to error (SSE)?f. Test whether of not there is a significant relationship between the monthly expenditure on food and the independent variables. Use a .01 level of significance. Be sure to state the null and alternative hypotheses.g. Compute the coefficient of determination and explain its meaning.h. Estimate the monthly expenditure on food for a family that has 4 members, eats out 3 times, and does not have any member of the family on a diet.i. At 95% confidence determine which parameter is not statistically significant.

Q: A sample of 30 houses that were sold in the last year was taken. The value of the house (y) was estimated. The independent variables included in the analysis were the number of rooms (x1), the size of the lot (x2), the number of bathrooms (x3), and a dummy variable (x4), which equals 1 if the house has a garage and equals 0 if the house does not have a garage. The following results were obtained:ANOVAdfSSMSFRegression204,242.8851,060.72Error205,890.008,235.60CoefficientsStandard ErrorIntercept15,232.58,462.5x12,178.4778.0x27.82.2x32,675.22,229.3x41,157.8463.1a. Write out the estimated equation.b. Interpret the coefficient on the number of rooms (x1).c. Interpret the coefficient on the dummy variable (x4).d. What are the degrees of freedom for the sum of squares explained by the regression (SSR) and the sum of squares due to error (SSE)?e. Test whether or not there is a significant relationship between the value of a house and the independent variables. Use a .05 level of significance. Be sure to state the null and alternative hypotheses.f. Test the significance of x1at the 5% level. Be sure to state the null and alternative hypotheses.g. Compute the coefficient of determination and interpret its meaning.h. Estimate the value of a house that has 9 rooms, a lot with an area of 7,500, 2 bathrooms, and a garage.

Q: The following regression model has been proposed to predict sales at a furniture store. = 10 " 4x1+ 7x2+ 18x3wherex1= competitor's previous day's sales (in $1,000s)x2= population within 1 mile (in 1000s)x3= 1 if any form of advertising was used, 0 if otherwise = sales (in $1,000s)a. Fully interpret the meaning of the coefficient of x3.b. Predict sales (in dollars) for a store with competitor's previous day's sale of $3,000, a population of 10,000 within 1 mile, and six radio advertisements.

Q: The Very Fresh Juice Company has developed a regression model relating sales (yin $10,000s) with four independent variables. The four independent variables are price per unit (x1, in dollars), competitor's price (x2, in dollars), advertising (x3, in $1,000s) and type of container used (x4where 1 = Cans and 0 = Bottles). Part of the regression results are shown below:Source of VariationDegrees of FreedomSum of SquaresMean SquareFRegression4283,940.60Error18621,735.14Totala. Compute the coefficient of determination and fully interpret its meaning.b. Is the regression model significant? Explain what your answer implies. Let = 0.05.c. What has been the sample size for this analysis?

Q: The Natural Drink Company has developed a regression model relating its sales (yin $10,000s) with four independent variables. The four independent variables are price per unit (PRICE, in dollars), competitor's price (COMPRICE, in dollars), advertising (ADV, in $1,000s) and type of container used(CONTAIN; 1 = Cans and 0 = Bottles). Part of the regression results is shown below. (Assume n = 25)CoefficientStandard ErrorIntercept443.143PRICE-57.17020.426COMPRICE27.68119.991ADV0.0250.023CONTAIN-95.35391.027a. If the manufacturer uses can containers, his price is $1.25, advertising $200,000, and his competitor's price is $1.50, what is your estimate of his sales? Give your answer in dollars.b. Test to see if there is a significant relationship between sales and unit price. Let = 0.05.c. Test to see if there is a significant relationship between sales and advertising. Let = 0.05.d. Is the type of container a significant variable?Let = 0.05.e. Test to see if there is a significant relationship between sales and competitor's price. Let = 0.05.

Q: The following is part of the results of a regression analysis involving sales (yin millions of dollars), advertising expenditures (x1in thousands of dollars), and number of salespeople (x2) for a corporation. The regression was performed on a sample of 10 observations.CoefficientStandard ErrorIntercept40.007.00x18.002.50x26.003.00a. If the company uses $40,000 in advertisement and has 30 salespersons, what are the expected sales? Give your answer in dollars.b. At = 0.05, test for the significance of the coefficient of advertising.c. At = 0.05, test for the significance of the coefficient of the number of salespeople.

Q: A microcomputer manufacturer has developed a regression model relating his sales (yin $10,000s) with three independent variables. The three independent variables are price per unit (Price in $100s), advertising (Adver in $1,000s) and the number of product lines (Lines). Part of the regression results is shown below.ANOVAdfSSMSFRegression2708.61Error142840.51CoefficientsStandard ErrorIntercept1.021122.8752Price-0.15240.1411Adver0.88490.2886Lines-0.14631.5340a. Use the above results and write the regression equation that can be used to predict sales.b. If the manufacturer has 10 product lines, advertising of $40,000, and the price per unit is $3,000, what is your estimate of their sales? Give your answer in dollars.c. Compute the coefficient of determination and fully interpret its meaning.d. At = 0.05, test to see if there is a significant relationship between sales and unit price.e. At = 0.05, test to see if there is a significant relationship between sales and the number of product lines.f. Is the regression model significant? (Perform an Ftest.)g. Fully interpret the meaning of the regression (coefficient of price) per unit that is, the slope for the price per unit.h. What has been the sample size for this analysis?

Q: In a regression model involving 46 observations, the following estimated regression equation was obtained. = 17 + 4x1" 3x2+ 8x3+ 5x4+ 8x5For this model, SST = 3410 and SSE = 510.a. Compute the coefficient of determination.b. Perform an Ftest and determine whether or not the regression model is significant.

Q: A regression model involving 8 independent variables for a sample of 69 periods resulted in the following sum of squares.SSE = 306SST = 1800a. Compute the coefficient of determination.b. At = 0.05, test to determine whether or not the model is significant.

Q: A regression model involving 3 independent variables for a sample of 20 periods resulted in the following sum of squares.Sum of SquaresRegression90Residual (Error)100a. Compute the coefficient of determination and fully explain its meaning.b. At = 0.05 level of significance, test to determine whether or not there is a significant relationship between the independent variables and the dependent variable.

Q: A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3are measured in thousands of dollars. The following results were obtained.ANOVAdfSSMSFRegression345.963464.28Error112.6218CoefficientsStandard ErrorIntercept0.0136x10.79920.074x20.22800.190x3-0.57960.920Coefficient of determination = 0.946a. Write out the estimated regression equation for the relationship between the variables.b. What can you say about the strength of this relationship?c. Carry out a test of whether yis significantly related to the independent variables. Use a .05 level of significance.d. Carry out a test to see if x3and yare significantly related. Use a .05 level of significance.e. Why would a coefficient of determination very close to 1.0 be expected here?

Q: A regression was performed on a sample of 20 observations. Two independent variables were included in the analysis, xand z. The relationship between xand zis z= x2. The following estimated equation was obtained. = 23.72 + 12.61x+ 0.798zThe standard errors for the coefficients are Sb1= 4.85 and Sb2= 0.21For this model, SSR = 520.2 and SSE = 340.6a. Estimate the value of ywhen x= 5.b. Compute the appropriate t ratios.c. Test for the significance of the coefficients at the 5% level. Which variable(s) is (are) significant?d. Compute the coefficient of determination and the adjusted coefficient of determination. Interpret the meaning of the coefficient of determination.e. Test the significance of the relationship among the variables at the 5% level of significance.

Q: The following results were obtained from a multiple regression analysis of supermarket profitability. The dependent variable, y, is the profit (in thousands of dollars) and the independent variables, x1and x2, are the food sales and nonfood sales (also in thousands of dollars).ANOVAdfSSMSFRegression2562.36311.23Error9225.326CoefficientsStandard ErrorIntercept-15.0620x10.09720.054x20.24840.092Coefficient of determination = 0.7139a. Write the estimated regression equation for the relationship between the variables.b. What can you say about the strength of this relationship?c. Carry out a test of whether yis significantly related to the independent variables. Use a .01 level of significance.d. Carry out a test of whether x1and yare significantly related. Use a .05 level of significance.e. How many supermarkets are in the sample used here?

Q: A regression was performed on a sample of 16 observations. The estimated equation is = 23.5 -14.28x1+ 6.72x2+ 15.68x3. The standard errors for the coefficients are Sb1= 4.2, Sb2= 5.6, and Sb3= 2.8. For this model, SST = 3809.6 and SSR = 3285.4.a. Compute the appropriate t ratios.b. Test for the significance of 1, 2, and 3at the 5% level of significance.c. Do you think that any of the variables should be dropped from the model? Explain.d. Compute R2and Ra2. Interpret R2.e. Test the significance of the relationship among the variables at the 5% level of significance.

Q: Below you are given a partial ANOVA table relating the price of a company's stock (yin dollars), the Dow Jones industrial average (x1), and the stock price of the company's major competitor (x2in dollars).Source of VariationDegrees of FreedomSum of SquaresMean SquareFRegressionError2040Total800a. What has been the sample size for this regression analysis?b. At = 0.05 level of significance, test to determine if the model is significant. That is, determine if there exists a significant relationship between the independent variables and the dependent variable.c. Determine the multiple coefficient of determination.

Q: Below you are given a partial Excel output based on a sample of 30 days of the price of a company's stock (yin dollars), the Dow Jones industrial average (x1), and the stock price of the company's major competitor (x2in dollars).CoefficientStandard ErrorIntercept20.0005.455x10.0300.010x2-0.700.200a. Use the output shown above and write an equation that can be used to predict the price of the stock.b. If the Dow Jones Industrial Average is 2650 and the price of the competitor is $45, what would you expect the price of the stock to be?c. At = 0.05, test to determine if the Dow Jones average is a significant variable.d. At = 0.05, test to determine if the stock price of the major competitor is a significant variable.

Q: Below you are given a partial ANOVA table based on a sample of 12 observations relating the number of personal computers sold by a computer shop per month (y), unit price (x1in $1,000) and the number of advertising spots (x2) they used on a local television station.Source of VariationDegrees of FreedomSum of SquaresMean SquareFRegression2655.955Error9Total838.917a. At = 0.05 level of significance, test to determine if the model is significant. That is, determine if there exists a significant relationship between the independent variables and the dependent variable.b. Determine the multiple coefficient of determination.c. Determine the adjusted multiple coefficient of determination.