Concept explainers
The data below were obtained from a creep test performed atroom temperature on a wire composed of 40% tin, 60% lead, andsolid core solder. This was done by measuring the increase in strainover time while a constant load was applied to a test specimen. Using a linear regression method, find (a ) the equation of these line that bestfits these data and (b ) the
If the line does not pass through the origin, force it to do so. Does thisnew line represent the data trend? Suggest a new equation that satisfies zero strain at zero time and also represents the data trend well.
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EBK NUMERICAL METHODS FOR ENGINEERS
- XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict the stock price to be in January 2012? January 2013?arrow_forwardbThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.arrow_forwardDoes Table 1 represent a linear function? If so, finda linear equation that models the data.arrow_forward
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- help ASAParrow_forward2. A sample of small cars was selected to attempt to use the horsepower (x) in hp of the car to predict the fuel efficiency (y) in miles per gallon. A researcher fitted a linear regression model. ŷ-44.0 -0.150x a) Interpret the slope of the regression line. b) Find the predicted fuel efficiency for a horsepower of 150 hp? c) If the fuel efficiency for a car of horsepower of 150hp had an actual fuel efficiency of 25mpg, what is the residual (error) for this car? d) Calculate the correlation coefficient. e) What is the strength of the correlation coefficient? R²=68% f) Interpret the y-intercept.arrow_forwardThe prices of Rawlston, Inc. stock (y) over a period of 12 days, the number of shares (in 100s) of the company's stocks sold (x1), and the volume of exchange (in millions) on the New York Stock Exchange (x2) are shown below. 1. Use Excel and write an equation that can be used to predict the price of the stock. 2. Interpret the coefficients of the estimated regression equation that you found in part (1). 3. Perform a t test and determine whether independent variable and dependent variable are related. Fully interpret the meaning. Use α = .05. 4. Perform an F test and determine whether independent variable and dependent variable are related. Fully interpret the meaning. Use α = .05 5. Conduct Residual Analysis and fully interpret the meaning. 6. If on a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 10 million, what would you expect the price of the stock to be? 7. Submit Excel document with steps…arrow_forward
- The prices of Rawlston, Inc. stock (y) over a period of 12 days, the number of shares (in 100s) of the company's stocks sold (x1), and the volume of exchange (in millions) on the New York Stock Exchange (x2) are shown below. 1. Use Excel and write an equation that can be used to predict the price of the stock. 2. Interpret the coefficients of the estimated regression equation that you found in part (1). 3. Perform a t test and determine whether independent variable and dependent variable are related. Fully interpret the meaning. Use α = .05. 4. Perform an F test and determine whether independent variable and dependent variable are related. Fully interpret the meaning. Use α = .05 5. Conduct Residual Analysis and fully interpret the meaning. 6. If on a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 10 million, what would you expect the price of the stock to be? 7. Submit Excel document with steps…arrow_forwardThe age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150arrow_forwardConsider the multiple regression model to investigate the relationship between the number of fishes (Y) per section of the stream and the following independent variables: dissolved oxygen (3 < oxy < 10, in mg/liter), maximum depth (1 < maxdepth < 8, in feet), and water temperature (5< temp < 20, in °C). The location of the stream was also considered (lowland and upland). Y-hat = 23.09 + 0.199*oxy + 0.3361*maxdepth +8.6730*temp + 3.8290* lowland. Which of the following is(are) TRUE about the estimated regression coefficient for location of the stream? 1. The location of the stream is a categorical variable, so it is represented by a dummy variable with upland stream as the reference variable. II. Holding other factors constant, the number of fishes in lowland is 3.8290 higher than upland streams. O A. I only O B. II only O C. Both I and II O D. Neither I nor IIarrow_forward
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