5. The following output from R presents the results from computing a linear model. In our data example we are interested to study the relationship between TV budget and sales This R output is for a simple data set that contains, in thousands of dollars, TV budget for 200 different markets along with the Sales, in thousands of units, for each market. summary (model1) ## ## Call: ## Lm (formula = Sales - TV, data = train) ## ## Residuals: ## Min 10 Median 30 Маx ## -8.5816 -1.7845 -0.2533 2.1715 6.9345 ## ## Coefficients: Estimate Std. Error t value Pr(>|t|) ## (Intercept) 6.764098 0.607592 11.13 <2e-16 ***k ## TV 0.050284 0.003463 14.52 <2e-16 *** ## -- ## Signif. codes: O '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 '' 1 #2# ## Residual standard error: 3.204 on 120 degrees of freedom ## Multiple R-squared: 0.6373, Adjusted R-squared: 0.6342 ## F-statistic: 210.8 on 1 and 120 DF, p-value: < 2.2e-16 confint(model1) ## 2.5 % 97.5 % ## (Intercept) 5.56110868 7.96708701 ## TV 0.04342678 0.05714057 a. Compute the standard deviation of errors. b. Construct a 95% confidence interval for slope B1. c. Using alpha=0.05, test whether B, is different from zero

5. The following output from R presents the results from computing a linear model. In our data example we are interested to study the relationship between TV budget and sales This R output is for a simple data set that contains, in thousands of dollars, TV budget for 200 different markets along with the Sales, in thousands of units, for each market. summary (model1) ## ## Call: ## Lm (formula = Sales - TV, data = train) ## ## Residuals: ## Min 10 Median 30 Маx ## -8.5816 -1.7845 -0.2533 2.1715 6.9345 ## ## Coefficients: Estimate Std. Error t value Pr(>|t|) ## (Intercept) 6.764098 0.607592 11.13 <2e-16 k ## TV 0.050284 0.003463 14.52 <2e-16 ## -- ## Signif. codes: O '' 0.001 '' 0.01 '' 0.05 '.' 0.1 '' 1 #2# ## Residual standard error: 3.204 on 120 degrees of freedom ## Multiple R-squared: 0.6373, Adjusted R-squared: 0.6342 ## F-statistic: 210.8 on 1 and 120 DF, p-value: < 2.2e-16 confint(model1) ## 2.5 % 97.5 % ## (Intercept) 5.56110868 7.96708701 ## TV 0.04342678 0.05714057 a. Compute the standard deviation of errors. b. Construct a 95% confidence interval for slope B1. c. Using alpha=0.05, test whether B, is different from zero

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The following output from R presents the results from computing a linear model. In our data example we are interested to study the relationship between TV budget and sales This R output is for a simple data set that contains, in thousands of dollars, TV budget for 200 different markets along with the Sales, in thousands of units, for each market. summary (model1) ## ## Call: ## Lm (formula = Sales TV, data = train) ## ## Residuals: ## Min 10 Median 30 Max ## -8.5816 -1.7845 -0.2533 2.1715 6.9345 ## ## Coefficients: ## Estimate Std. Error t value Pr(>|t|) ## (Intercept) 6.764098 ## TV 0.607592 11.13 <2e-16 ***k 0.050284 0.003463 14.52 <2e-16 *** ## --- O '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 ## Signif. codes: #2# ## Residual standard error: 3.204 on 120 degrees of freedom ## Multiple R-squared: 0.6373, Adjusted R-squared: 0.6342 ## F-statistic: 210.8 on 1 and 120 DF, p-value: < 2.2e-16 confint (model1) ## 2.5 % 97.5 % ## (Intercept) 5.56110868 7.96708701 ## TV 0.04342678…
Example 31. Plot Less than Ogive and More than Ogive for the following data: Cost of production 4 - 6 6 - 8 8 – 10 10 – 12 12 – 14 14 – 16 | No. of farms 13 111 182 105 19
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Examine attached graph. What relationship (positive, negative, none) is obsevred between economic (i) economic growth and unemployment, (i) economic growth and inflation and (iii) unemployment and inflation from the period 2009 to 2018? Justify your response. Complete the following table: Variables Relationship Justification (i) economic growth and unemployment (ii) economic growth and inflation (iii) unemployment and inflation
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams Vitamin C content in mg 55 11.9 60 13.7 65 15.9 70 18.5 75 20.8 80 23 85 25.8 A) Find the regression equation: places y= + Round your answers to 3 decimal B) Answer the following questions using your un-rounded regression equation. If we test 115 grams of raspberries what is the expected Vitamin C content? nearest tenth) mg (round to the
How much should a healthy Shetland pony weigh? Let x be the age of the pony (in months), and let y be the average weight of the pony (in kilograms). x 3 6 12 20 26 y 60 95 140 160 189 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. Flash Player version 10 or higher is required for this question. You can get Flash Player free from Adobe's website. (b) Would you say the correlation is low, moderate, or strong? low moderate strong Would you say the correlation is positive or negative? positive negative (c) Use a calculator to verify that x = 67, x2 = 1265, y = 644, y2 = 93,546, and xy = 10,544. Compute r. (Round your answer to three decimal places.) As x increases from 3 to 26 months, does the value of r imply that y should tend to increase or decrease? Explain your answer. Given our value of r, y should…
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams 50 60 70 80 90 100 110 Vitamin C content in mg 9.3 14.3 18.9 23.5 27.5 31.7 36.9 A) Find the regression equation: y = places x + Round your answers to 3 decimal B) Answer the following questions using your un-rounded regression equation. If we test 140 grams of raspberries what is the expected Vitamin C content? nearest tenth) mg (round to the
Objective [2.6] Situation: The Ipod Touch has been out for two years now and a lot of data has been collected. Relevant Relationship: There is a functional relationship between Price of an IPod Touch,p and Weekly Demand,s. Below is a table of data that have been collected Price,p,($) Weekly Demand, s,(1,000s) 150 170 190 210 230 250 215 202 198 188 178 171 A.. Find the linear model that best fits this data using regression and enter the model below (for entry round the linear parameter value to nearest 0.01 and constant parameter to nearest 1) S = T(p) = B. The squared correlation coefficient was Select an answer 0.95 (note: values less than 0.95 MAY mean the model is not appropriate for making predictions) Now answer these two questions using the UNROUNDED model parameters C. What does the model predict will be the weekly demand if the price of an ipod touch is $235 ? (nearest 100) D. According to the model at what should the price be set in order to have a weekly demand of 202,800…
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. Vitamin C content in mg grams 45 7.3 55 11.5 65 15.9 75 20.3 85 25.8 95 29.2 105 33.9 A) Find the regression equation: y = Round your answers to 3 decimal places B) Answer the following questions using your un-rounded regression equation. If we test 135 grams of raspberries what is the expected Vitamin C content? mg (round to the nearest tenth)
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I need expert advice please especially with the graph. The table below shows monthly data collected on production costs and on the number of units produced over a twelve month period. Month Total Production Costs Level of Activity(Units Produced) July $230,000 3,500August 250,000 3,750September 260,000 3,800October 220,000 3,400November 340,000 5,800December 330,000 5,500January 200,000 2,900February 210,000 3,300March 240,000…
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. Round your answers to 3 decimal places y= Raspberry Type Farm A - North Field Farm B - North Field Farm A - South Field Farm B - South Field Farm C -Small Field Farm D Farm E x+ grams 60 65 70 75 80 85 90 Vitamin C content in mg 14.3 16.1 18.9 20.3 22.8 25.5 27.5 According to this model, how many mg of Vitamin C can be expected in a raspberry that weighs 82 grams Round to 3 decimal places.