1. INTRODUCTION Obesity is a growing concern in today's society, with factors such as family history and ethnicity playing a role in determining an individual's weight. In this research, we aim to investigate how physical activities, genetics, and diet impact weight through the use of linear regression analysis. 2. MODEL DESCRIPTION We will be using the following model to analyze the relationship between weight and various factors: \[ y_{i} = \beta_{0} + \beta_{1} x_{i1} + \beta_{2} x_{i2} + \beta_{3} x_{i3} + \varepsilon_{i} \] Where: - \( y_{i} \) represents the weight in pounds of individual \( i \) - \( x_{i1} \) is a dummy variable representing the individual's genes - \( x_{i2} \) represents the amount of time spent on physical exercise in hours - \( x_{i3} \) represents the individual's daily calorie intake - \( \varepsilon_{i} \) is a random variable with a mean of 0 and variance of 1 3. DATA COLLECTION We have collected data from a sample of 50 individuals, with information on their weight, genes, exercise habits, and daily calorie intake. This data will be used to analyze the impact of these variables on weight. 4. COMPUTATIONAL To analyze the data and find the coefficients for the model, we will use SPSS. By running the regression analysis, we will be able to determine which variables have a significant impact on weight loss