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1. Open the excel attached.
2. Sample 50 rows following the instruction in the video (https://toptipbio.com/random-sampling-excel/) start at the 3 minute mark – using Method 2). You are to sample across all columns and then save the Excel Workbook as your own unique, personal dataset (Urfa Jamil.xlsx)
Select one (1) categorical and two (2) quantitative variables.Visualize and describe the distribution of each variable using appropriate methods in Excel. For each variable, separately provide:one visual (e.g. graph) – remember the principles of good graphing;
appropriate descriptive statistics;
a one-sentence description of the distribution of the variable. (See examples below.) Spot and describe outliers in the dataset. Do not remove!
Analyze the relationship between the two quantitative variables using the regression options in Excel. Identify which variable is the dependent variable (response) and which variable is the independent variable (explanatory). Provide:
• scatterplot – remember the principles of good graphing;
• appropriate statistics including the line of best fit (regression equation);
• description of the relationship between the two variables that includes the interpretation of correlation, slope and intercept, and the coefficient of determination; and finally a
• recommendation as to whether or not your model should be used for predictions.
Write a two-page Data Report based on your exploration using the following sections:Introduction that briefly states the purpose and contents of the report.
Data section describing the dataset. Methods section describing the choice of variables, visuals created, summary statistics calculated.
Analysis section that contains the required analyses from 5(a-c).
Conclusion giving the most relevant observations and interesting findings. The results of a statistical analysis should reinforce common sense
• Is the slope reasonable?
• Does the direction of the slope seem right?
• Always be skeptical and ask yourself if the answer is reasonable
Be Careful
• Don’t fit a straight line to a nonlinear relationship
• Beware of extraordinary points
– Look for y-values that stand off from the linear pattern
– Look for x-values that exert a strong influence
• Don’t extrapolate far beyond the data
• Don’t infer that x causes y just because there is a good linear model for
their relationship
• Don’t choose a model based on R2 alone
• Be sure to get the regression the right way around
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NB: We do not sell prewritten papers. All essays are written from scratch according to specific needs and instructions