STT500 Statistics for Decision Making

STT500 Assignment Help
Statistics for Decision Making Assignment help

Description Group of four students must provide a 2000-words to report the findings of your assignment plus video presentation will be prepared based on the material discussed. Your Group assignment will be prepared based on the material discussed and presented in weeks 8 to 11 lectures and tutorials. Consequently, the topics may include evaluation of hypotheses testing, Regression analysis and Time Series analysis. Please use Excel for statistical analysis in this assignment. Relevant Excel statistical output must be properly analysed and interpreted. Assignment Data Demonstrate your ability to perform statistical analysis of a data set. You will locate your
own data set; a great source of data is available at Kaggle (https://www.kaggle.com/ )
Your data must contribute to addressing the research objective/questions and cover the following:

• At least two continuous variables for analysis which must be a continuous variable.
• At least two grouping variables, each with two distinct categories. Assignment Questions Make sure the following questions are covered

in data analysis: 1) Create graphical analysis for numerical and categorical variables. Also Comment on the key findings. 2) For statistical analysis involving hypothesis test: Formulate the null and alternative hypotheses. State your statistical decision using the significant value (α) of 5%. 3) Evaluate the performance of simple linear Regression analysis based on the two numerical variables. You describe and explain your process for variable selection. Your choices are justified by Regression data analysis. 4) Check the model assumptions for the simple linear regression model and common violations. 5) Evaluate the performance of Multiple linear Regression analysis based on the three numerical variables. You describe and explain your process for variable selection. Your choices are justified by Regression data analysis. 6) Check the model assumptions for the multiple linear regression model and common violations. 7) Evaluate the performance of the simple linear regression (Model 1) and the multiple linear regression (Model 2). Check which model (Model 1 or Model 2) seems to fit better. 8) At the 0.05 level of significance, determine whether the independent variable makes a significant contribution to the simple linear regression model 1. 9) At the 0.05 level of significance, determine whether the independent variables make a significant contribution to the multiple linear regression model 2.
10) State your conclusion in context. When The assessment is due to be submitted by Sunday 29th January 2023, 11:59pm. This is to be submitted via the Turnitin similarity checking link. Format Submit either a Word document or a PDF for the group report and video presentation.