### Demand for Oil Changes at Garcia's Garage#### Monthly Data for Oil Change Demand| Month | Number of Oil Changes ||-----------|------------------------|| January | 38 || February | 55 || March | 66 || April | 60 || May | 58 || June | 61 || July | 70 || August | 52 |#### Analysis Task**Objective**: Use simple linear regression analysis to develop a forecasting model for monthly demand. - **Dependent Variable, \( Y \)**: Monthly demand (number of oil changes).- **Independent Variable, \( X \)**: Time period, expressed in months (e.g., January = 1, February = 2, ... August = 8).**Instructions**:1. For January, let \( X = 1 \).2. For February, let \( X = 2 \).3. Continue incrementing \( X \) by 1 for each subsequent month.The forecasting model is given by the equation:\[ Y = b_0 + b_1 \cdot X \]*(Enter your responses rounded to two decimal places.)*### Explanation of the TableThe provided table displays the number of oil changes recorded for each month from January to August. This data will serve as the basis for developing a predictive model using simple linear regression, which will allow us to forecast future demand based on the trend observed in the historical data.

Linear regression forecasting is a statistical technique used to predict or forecast future values…

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Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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