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Guide to Using Minitab For Basic Statistical Applications To Accompany Business Statistics: A Decision Making Approach, 6th Ed. Chapter 3: Describing Data Using Numerical Measures By Groebner, Shannon, Fry, & Smith Prentice-Hall Publishing Company Copyright, 2005 Chapter 3 Minitab Examples Population Mean Foster City Hotel Mean, Median,and Mode Weigh-In-Motion Percentiles and Quartiles Weigh-In-Motion Box and Whisker Plots Weigh-In Motion More Examples Chapter 3 Minitab Examples (continued) Measures of Variation Weigh-In-Motion Empirical Rule Burger N’ Brew Population Mean Foster City Hotel Issue: Determine the mean nightly revenue for the Foster City Hotel. Objective: Use Minitab to calculate the population mean revenue Data File is FosterCity.mtw Population Mean – Foster City Hotel Open the Minitab file called FosterCity.mtw Population Mean – Foster City Hotel Select Calc – Column Statistics Population Mean – Foster City Hotel Click on Mean and define the Input Variable for analysis Population Mean – Foster City Hotel Population Mean Population Mean – Foster City Hotel Second method: Select Stat, then Basic Statistics then Display Descriptive Statistics Population Mean – Foster City Hotel Select the variables to analyze Population Mean – Foster City Hotel Population Means Note, other output is also provided Mean, Median and Mode Weigh-In-Motion Issue: Does the WIM scale produce gross weights that are close to the POE weights? Objective: Use Minitab to develop histograms for the weights from each scale and to compute the mean, median, and mode for each scale. The data file is Trucks.mtw. Mean, Median, and Mode – Weigh-In-Motion Open the data file called Trucks.mtw Data File contains 200 trucks. Mean, Median, and Mode – Weigh-In-Motion Construct cutpoints column. Mean, Median, and Mode – Weigh-In-Motion Select Graph – Histogram to form the histograms for the POE and WIM gross weights Mean, Median, and Mode – Weigh-In-Motion Identify variables to be graphed and set Display to Bar Next, use Options to set class widths Mean, Median, and Mode – Weigh-In-Motion For Type of Intervals select Cutpoint, in Definitioin of intervals, insert Cutpoint column. Mean, Median, and Mode – Weigh-In-Motion Use Edit Attributes to Set Graph Colors, etc. Mean, Median, and Mode – Weigh-In-Motion Use Annotate to Set Graph Titles, etc. Mean, Median, and Mode – Weigh-In-Motion To modify X axis labeling, use Frame - Tic Mean, Median, and Mode – Weigh-In-Motion POE Gross Weight Histogram Completed Mean, Median, and Mode – Weigh-In-Motion Repeat the process for WIM gross weights. Then compute mean, median and modes for both variables Mean, Median, and Mode – Weigh-In-Motion Select Stat – then select Basic Statistics and Display Descriptive Statistics Mean, Median, and Mode – Weigh-In-Motion Select the variables to be analyzed Mean, Median, and Mode – Weigh-In-Motion Mean and Median Minitab does not compute the mode Percentiles and Quartiles Weigh-In-Motion Issue: Determine Percentiles and Quartiles for WIM and POE Gross Weights Objective: Use Minitab to calculate 10th percentiles and 1st and 3rd quartiles for weigh-in-motion data. Data file is Trucks.mtw Percentiles and Quartiles - Weigh-In-Motion Open the data file called Trucks.mtw Data File contains 200 trucks. Percentiles and Quartiles - Weigh-In-Motion Select Stat – then Basic Statistics – then Display Descriptive Statistics Percentiles and Quartiles - Weigh-In-Motion Define Variables for analysis Percentiles and Quartiles - Weigh-In-Motion 1st and 3rd quartiles for WIM and POE gross weights Percentiles and Quartiles - Weigh-In-Motion To obtain percentiles, Select Stat – Reliability/Survival –Parametric Dist Analysis Right Cens… Percentiles and Quartiles - Weigh-In-Motion Identify Variables for analysis – then click on Estimate Percentiles and Quartiles - Weigh-In-Motion Enter desired percentiles Percentiles and Quartiles - Weigh-In-Motion 1st and 3rd quartiles WIM Gross Weight WIM Gross Weight 10th Percentile Percentiles and Quartiles - Weigh-In-Motion 1st and 3rd quartiles POE Gross Weight POE Gross Weight 10th Percentile Box and Whisker Plots Weigh-In-Motion Issue: Analyze how WIM and POE gross weights compare. Objective: Use Minitab to develop a Box and Whisker Plot for comparing WIM and POE gross weights. Data file is Trucks.mtw Box and Whisker Plots - Weigh-In-Motion Open the data file called Trucks.mtw Data File contains 200 trucks. Box and Whisker Plots - Weigh-In-Motion Click on Graph – then select Character Graphs – then select Boxplot Box and Whisker Plots - Weigh-In-Motion Enter Variable for Analysis (WIM Gross Weight) Box and Whisker Plots - Weigh-In-Motion Box and Whisker Plot – WIM Gross Weight Box and Whisker Plots - Weigh-In-Motion Repeat process for Box and Whisker Plot – POE Gross Weight Measures of Variation Weigh-In-Motion Issue: Understand the Variation in POE and WIM gross Weights Objective: Use the Minitab to compute various measures of variation in WIM and POE Gross Weights Data file is Trucks.mtw Measures of Variation - Weigh-In-Motion Open the data file called Trucks.xls Data File contains 200 trucks. Measures of Variation - Weigh-In-Motion Click on Stat tab – then select Basic Statistics – then choose Display Descriptive Statistics Measures of Variation - Weigh-In-Motion Define variables to be included in the analysis Measures of Variation - Weigh-In-Motion Standard Deviation, Minimum and Maximum values Empirical Rule Burger N’ Brew Issue: Analyze the Phoenix Burger Sales Distribution Objective: Use the Minitab to compute graphs and numerical measures necessary for using the empirical rule to analyze sales at Burger N’ Brew Data file is BurgerNBrew.mtw Empirical Rule – Burger N’ Brew Open the data file called BurgerNBrew.mtw Data File contains sales for 365 days. Empirical Rule – Burger N’ Brew This tutorial will demonstrate a different way to develop a Histogram using class widths of 2. Select Graph Histogram Empirical Rule – Burger N’ Brew Identify variable for analysis – Then use Options to specify classes Empirical Rule – Burger N’ Brew Use class widths of size 2 Empirical Rule – Burger N’ Brew Use Annotate to specify titles etc. Empirical Rule – Burger N’ Brew Finished Histogram – Bell Shaped Distribution Empirical Rule – Burger N’ Brew To compute numerical measures – Click Stat – Basic Statistics – Display Descriptive Statistics Empirical Rule – Burger N’ Brew Identify variable for analysis Empirical Rule – Burger N’ Brew Mean and Standard Deviation Empirical Rule: 68% within 15.12 + (1)3.13 95% within 15.12 + (2)3.13 99.7% within 15.12 + (3)3.13)
