QUESTION 5Given the following information1. The linear regression trend line equation for the de-seasonlized data (Unadjusted):Ft=149+4t2. Seasonality Index tableSeasonality Index (SI)0.651.56PeriodYear2021-period 12021-period 22021-period 316202117180.91Find the Adjusted Forecast in year 2022 for Period= 1(Rounti your answer to 2 decimal places)

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Answered: QUESTION 5 Given the following…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter6: Exponential And Logarithmic Functions

Section6.8: Fitting Exponential Models To Data

Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...

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Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
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Question 6Finally, the researcher considers using regression analysis to establish a linear relationship between the two variables – hours worked per week and yearly income.a) What is the dependent variable and independent variable for this analysis? Why?b) Use an appropriate plot to investigate the relationship between the two variables. Display the plot. On the same plot, fit a linear trend line including the equation and the coefficient of determination R2.c) Estimate a simple linear regression model and present the estimated linear equation. Display the regression summary table and interpret the intercept and slope coefficient estimates of the linear model.d) Display and interpret the value of the coefficient of determination, R-squared (R2).
Question 4 - 6 refer to following variables: Dependent variable: Sentence Months Independent variable: Year of Education After calculating the regression slope of the two variables, explain what the slope refers to by selecting two correct answers (NO PATIAL CREDIT). Form: For one unit increase in [a], [b] is predicted to [c] by the slop. For one unit increase in Sentence Months, For one unit increase in Year of Education, Sentence Months is predicted to increase by the slop Sentence Months is predicted to decrease by the slop Year of Education is predicted to increase by the slop Year of Education is predicted to decrease by the slop
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Ch 13. 7: Refer to the Lincolnville School District bus data. First, add a variable to change the type of engine (diesel or gasoline) to a qualitative variable. If the engine type is diesel, then set the qualitative variable to 0. If the engine type is gasoline, then set the qualitative variable to 1. Develop a regression equation using statistical software with maintenance cost as the dependent variable and age, odometer miles, miles since last maintenance, and engine type as the independent variables.
Section 10.2 Question #7 Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85mm Hg. Use a significance level of 0.05. Right Arm 103 102 96 79 79 Left Arm 174 167 147 143 145 View the critical values of the Pearson correlation coefficient r Data table Dialog content starts Critical Values of the Pearson Correlation Coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0,reject H0 if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576…
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Question # 1 A well-known multinational FMCG produces more than fifty products and sells them in the market. Out of fifty products one is mineral water for drinking purpose and supplies different size pack bottles in the market. Product manager observed that, during hot days the sale of water is more as compared to the normal days. He started the collection of data of weekly sale of water and the average weekly temperature. Product manager was interested in developing a relationship between sales and temperature; therefore, he discussed and shared the following data with you. sales 75 77 69 63 79 80 77 70 73 87 72 73 80 80 69 84 77 72 74 81 temperature 32 36 31 31 34 29 32 35 28 31 30 31 29 35 36 28 32 33 32 33 Sale is in thousand liters and temperature is in degree Celsius. Data…

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