Restaurant Dinner Price ($) (QN 1) Luch Price ($) (QN 2) Quality Rating (QL) 3 28 20 Good 6 28 20 Good 9 23 16 Very Good 12 44 31 Very Good 15 25 18 Good 18 17 12 Excellent 21 33 23 Very Good 24 33 23 Excellent 27 27 19 Good 30 34 24 Very Good 33 44 31 Excellent 36 10 7 Good 39 15 11 Good 42 45 32 Excellent 45 40 28 Excellent 48 20 14 Very Good 51 38 27 Very Good 54 21 15 Excellent 57 25 18 Excellent60 10 Good 63 35 25 Very Good 66 40 28 Excellent 69 12 8 Very Good 72 36 25 Very Good 75 18 13 Very Good 78 25 18 Very Good 81 21 15 Very Good 84 23 16 Good 87 11 8 Good 90 20 14 Excellent2022 Project Part I5 Correlation, Regression, and Prediction Points on Rubric: 20 Submit as a le upload For this portion of the project. use the data from your two quantitative variables to estimate the best fitting line through your data. Select one of your variables (the one you would like to predict) as the dependent variable, \"y\" and the other variable as the independent variable,\" x\". You can use Excel. Stat crunch or a 1183.984 calculator to perform a linear regression analysis. If you are using a computer program. such as Excel or Stat Crunch. you may want to copys'paste your regression table results into your report. If you are using Excel. there is an option to display the \"trend line\" with the equation and Rsq. value directly on the scatterplot. Your project should be submitted in a semi-professional looking report. preferably typed in Word. Include the following in your report. 1. Introduction: Briey describe your sample and your two quantitative variables, including their units of measurement. State that the purpose of your analysis is to use linear regression to predict "y\" (ll in what your "y variable" is) for any given value of \"x" (ll in What your x variable is). 2. Insert a scatter plot. Make sure your \"x" (independent) variable is on the \"x- axis" and the \"y\" (dependent) variable is on the 'y-axis". 3. Find & practically interpret the correlation coefficient (r) 4. Find & practically interpret the coefcient of determination (R) 5. Find the equation on of the leastsquares line (be specic ) 6. Find & practically interpret the slope (be specic ) 7. Find & interpret the yintereept if an interpretation is possible. If it's not possible. just report the yintercept and explain why it cannot be interpreted practically 8. Brief conclusion or discussion of the results (e.g. assumptions, potential problems, are the results what you expected? use the model to make a prediction, etc.) Note: Regression line. line of best t. and least-squares line all refers to the same thing. Suggestions: Take a moment to think about which variable you would like to make your dependent (y) variable and which variable you would like to make your independent (x) variable. The y variable is the one you would like to predict based on it. Make a note of which one you selected for y and which for x. then when going through your interpretations, don't mix them up. There is a tutorial on how to create scatter plots and nd the least-squares regression line in Stat Crunch and Excel. While the tutorial will walk you through how to get your results, it does not Show you how to do the interpretations. I would recommend re-watching the videos on regression (or viewing the example attached). In Stat Crunch. there is an option to \"group by" when doing a regression analysis. Do NOT use this option