Consider the following time series:QuarterYear 1Year 2Year 3807465696151485043687182a. Construct a time-series plot. What type of pattern exists in the data? Is there an indicationof a seasonal pattern?b. Use multiple linear regression model with dummy variables as follows to develop anequation to account for seasonal effects in the data. Qtrl = 1 if quarter 1,0 else; Qtr2 = 1 ifquarter 2,0 else; Qtr3 = 1 if quarter 3,0 else.c. Compute the quarterly forecasts for next year.

a. The time-series plot is obtained using Excel as; 1. Enter the data into spreadsheet. 2. Go to…

Answered: Consider the following time series:…

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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KidsFeet Regression Line y-Intercept The KidsFeet dataframe contains data collected on 39 fourth grade students in Ann Arbor, MI, in October 1997. Two of the measurements taken on the children were the length in centimeters, (length), and width in centimeters, (width), of their longest foot. This data could be used to answer the following Research Question: How is the width of a fourth-grade student's foot related to the length? Which of the following is the y-intercept of the regression line? ## ## Simple Linear Regression## ## Correlation coefficient r = 0.6411 ## ## Equation of Regression Line:## ## length = 9.817 + 1.658 * width ## ## Residual Standard Error: s = 1.025 ## R^2 (unadjusted): R^2 = 0.411 ( ) 1.0248 ( ) 1.6576 ( ) 22.8153 ( ) 0.411 ( ) 9.8172 ( )0.6411
Tuition($) Applicant Pool Applicant 950 76210 11040 1225 78000 10940 1325 67420 8670 1350 70380 9040 1500 62580 7410 1675 59260 7080 1800 57930 6350 1975 60130 6110 a. Using POMQM, develop the multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Determine the forecast for freshman applicants for a tuition rate of $1700 per semester, with a pool of applicants of 63000.
Editor of Astrology Magazine wants to obtain sales forecast value for 2021. Use the given data below and help the editor. Year Quarter Sales 2019 1. 53 2. 51 3. 48 4. 55 2020 1. 53 2. 51 3. 54 4. 52 Use time series regression model and determine sales forecast value for the second quarter of 2021
An instructor asked a random sample of eight students to record their study times at the beginning of a course. She then made a table for total hours studied (x) over 2 weeks and test score (y) at the end of the 2 weeks. The table is given below. Complete parts (a) through (f). x 10 13 10 18 6 15 16 21 y 93 79 81 74 85 81 85 80 a. Find the regression equation for the data points. b. Graph the regresson equation c. Describe the apparent relationship between the two variables. d. Identify the predictor and response variables. e. Identify outliers and potential influential observations. f.Predict the score for a student that studies for 17 hours.
Tuition($) Applicant Pool Applicant 950 76210 11040 1225 78000 10940 1325 67420 8670 1350 70380 9040 1500 62580 7410 1675 59260 7080 1800 57930 6350 1975 60130 6110 a. Using POMQM, develop the multiple regression equation for these data. b. What is the coefficient of determination for this regression equation? c. Determine the forecast for freshman applicants for a tuition rate of $1700 per semester, with a pool of applicants of 63000. CAN YOU SHOW ME ALL THE ANSWER WİTH EXCELL TABLE
a) Determine the least squares regression equation for the population in years since 2005. Round the slope and y-intercept to the nearest tenth. b) Find the correlation coefficient, r-value, of the line. Round your answer to the nearest thousandth. c) Predict the population for the 2020. ____ thousand people
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. The equation of the regression line is y = 1.454x- 36.984. Wages (state), x Wages (federal), y 712 778 789 801 843 878 927 937 939 958 1,014 1,054 1,116 1,146 1,191 1,248 1,270 1,302 1,335 1,401 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 95% confident that when the average weekly wages of state government employees is $895, the average weekly wages of federal government employees will be between $ and…
b. Add in the table provided in the spreadsheet a dummy variable that takes the value of 1in the fourth quarter of each year and show the table with all the data c. Using the data provided in the spreadsheet including the dummy variable you have created for the fourth quarter of each year run a regression with dependent variable the CBC house price index and independent variables the other three variables (Nominal GDP, Number of Households, and the dummy variable for the fourth quarter). Present the typical regression results output for this regression produced by Excel. d. Explain what the particular numbers for the following statistics that you presented in b) mean (no points will be given if you write general definitions without interpreting the particular numbers that you have presented): a. R-squared b. The t-statistics of the three independent variables c. The coefficients of the three independent variables e. Discuss if the signs that you get for the coefficients of each of the…
Which of the following statements best describes linear regression? A measure of the degree of dependence between two variables. A statistical technique using pairs of data and identifying a line which ‘best fits’ all of the pairs of observations. A measure of the proportion of changes in the dependent variable which can be explained by a change in the independent variable. Shows individual costs against their associated activity levels but makes no attempt to identify a linear relationship between them.
Use R programming or excel to answer the following. Visualize your answers. Consider the following quarterly time series: Quarter Year 1 Year 2 Year 3 1 923 1112 1243 2 1056 1156 1301 3 1124 1124 1254 4 992 1078 1198 Construct a time series plot. What type of pattern exists in the data? Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. Compute the quarterly forecasts for next year based on the model developed in part b.

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