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American Institute of Pharmaceutical Technology Regression Analysis and ANOVA

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, 2nd degree polynomial, and 3rddegree 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 R2 value. 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, 2nd degree polynomial, and 3rd 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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