Statistics (Essay Sample)

Course Reflection Department name, Institution name Course number: Course name Instructor’s name Due date Course Reflection I have enjoyed the multiple regression the most throughout the last five sessions. It perfectly extends the two-variable concepts to the scenario that involves one criterion variable (Y) and many independent features of a dataset (Dretzke, 2013, p.210). Excel enables analysts to put as many as 16 predictor variables. A model that includes three variables is as follows: Y=B0+B1X1+B2X2+B3X3 I enjoyed the multiple regression because I could predict dependent variable values based on the constants. For instance, I can easily forecast the price of bitcoin based on factors such as market demands and the cost of other competing currencies. Additionally, the business can predict the salesperson's sales volume from the Sale Aptitude test score. Therefore, multiple regression efficiently assesses the strength between outcome variables and several predictor features. The first step of the data analysis, which is the data cleaning and preparation, is an area that I struggled with and was challenging because knowing the dataset sample enough to answer a research question can be difficult. For instance, having messy data due to high volume can cause problems for the analyst. Additionally, Deciding whether to remove the missing values or replace them with a deal like the mean is challengin...