Manufacturing

Table of Contents
Executive Summary 3

Objective 3

Method 3

Procedure 3

Basic Data Analysis 4
Exploratory Data Analysis 4

Simple Linear Analysis 4 t-Test 4
Coefficients of Determination 5
Scatter Diagrams 5
Residual Analysis 5
Conclusion 6

Multiple Regression Analysis – Two Variables 6 f-Test 6 t-Test 6
Coefficients of Multiple Determination 7
Residual Analysis for the Multiple Regression Model 7
Conclusion 8

Multiple Regression Analysis – Three Variables 9 f-Test 9 t-Test 9
Coefficients of Multiple Determination 9
Residual Analysis for the Multiple Regression Model 9
Conclusion 10

Interaction Terms 10

Stepwise Regression 11

Using the Multiple Regression Model 11
Multiple Regression Equation 11
Example 12
Example Considering Location 12

Executive Summary
Using both linear and multiple regression analysis on the information gather by Zagat’s Restaurant Rating in New York City and Long Island to determine and predict the value of price based on the following factors: restaurant décor, service, location and food. Multiple models will be tested to determine which independent variables have the strongest relationship with price. After analyzing multiple models and determining the most significant model, this information will be passed on to restaurant owners to help their restaurants decide pricing for their dishes in the future.

Objective
The objective is to analyze the data of 106 restaurants that Zagat’s Restaurant Ratings has provided to conclude which independent variables are critical and how they affect the pricing strategy of restaurants. The data from Zagat’s will include the following: décor, service, location and quality of food.

Method
Calculations were