American Institute of Pharmaceutical Technology Regression Analysis and ANOVA

Question Description

Problem 1: Using the data in the Excel file Student Grades, construct a scatter chart for midterm versus final exam grades and add a linear trendline. What is the model? If a student scores 75 on the midterm, what would you predict her grade on the final exam to be?
- Label the scatterplot and report the equation of your model in addition to clearly answering the question about your prediction of her grade.
Problem 3: Each worksheet in the Excel file LineFit Data contains a set of data that describes a functional relationship between the dependent variable y and the independent variable x. Construct a line chart of each data set and use the Trendline tool to determine the best-fitting functions to model these data sets. Do not consider polynomials beyond the third degree.For each dataset, use the Trendline tool to find the linear, exponential, 2^nd degree polynomial, and 3^rddegree polynomial model. Identify the best model out of these four choices. Construct a labeled scatterplot for each dataset that reports your chosen best model and its R²value. For the first dataset, you won’t be able to do an exponential graph because some of the values are negative. For the first dataset, just compare linear, 2^nd degree polynomial, and 3^rd degree polynomial. For the second and third dataset, do all four. Problem 11: The Excel file National Football League provides various data on professional football for one season. a. Construct a scatter diagram for points/game and yards/game in the Excel file. Does there appear to be a linear relationship? b. Use the Regression tool to develop a model for predicting points/game as a function of yards/ game. Explain the statistical significance of the model and the R2 value.The points/game variable is the dependent variable (y-variable). Do not worry about explaining the significance of the model, just interpret the R² value in context. Write out the equation of your model in a labeled blank cell. Label your scatterplot.For the previous question in part C, interpret the slope of the model in context.

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