1. Chance Demonstrations.  Coincidence (Runs, Clusters, Birthday problem),  Four Envelope problem,  Law of Very Large Numbers

2. Surveys: These help people evaluate their strengths and opportunities for improvement in various aspects of statistical literacy 

3. Describe & Compare Percentages and Rates using Ordinary English.

4. Standardizing:  Using graphs, these web programs show users the impact of controlling for a related factor. 

5. Part-whole Grammar Reading and Writing Drills: This web programs help users develop their skills in using ordinary English to describe and compare rates and percentages as presented in pie charts, in statements, in tables and in graphs.   The author (Tom Burnham) of these cutting-edge programs is shown above.

6. Odysseys2sense: A lively game of civil discourse.

7. Using Excel pivot tables to create summary statistics

8. Model Data Using Excel

9. Create Histograms using Excel

10. Create Discrete Distributions using Excel

11. Create Log-Normal Distributions using Excel

12. Create Distributions Empirically using Excel

13. Create Sampling Distributions using Excel

14. Create and Compare Confidence Intervals using Excel.

15. Simple Models for Statistical Significance

16. Create Hypothesis Tests using Excel

• Uploading into Canvas  Schield Fall 2022.   Videos:  Slides1  Slides2.  Odyssey Grades:  Slides
• PowerPoint: Create Audio and Video.  Schield 8/2020.  Slides
• Edit/Convert Zoom Video Recording using AVS Software.  Schield (7/2020)
• Google Drive: Share Content.  Schield (2020)  Slides
• ResearchGate: Replace File.  Schield (2020) 
• Review of Association Grammar.  Schield 2019.
• Generating High Resolution Pictures from Visio 2003.  Schield (2017)

1. CHANCE-COINCIDENCE DEMONSTRATIONS:

• Coincidence: Random Letters Create Words.   Schield (2020) Excel demo. 
• Coincidence: Runs of Heads w Fair Coin (1 chance in 2).   Schield Excel demo.  For details, see Coincidence  (Schield 2012).
• Coincidence: Clusters of Rice (1 chance in 100).    Schield Excel demo.  For details, see Coincidence  (Schield 2012).
• Coincidence: von Mises Birthday Problem.   Schield Excel demo. 
  For details, see Coincidence (Schield 2012).  See also Santos-Dias 2014 slides
• Marilyn vos Savant's "Monty-Hall Three Door Problem".  Schield Excel demonstration.
• Marilyn vos Savant's "Four Envelope Problem".  Schield Excel demonstration.
• Law of Very Large Numbers: "Unlikely is almost certain given enough tries".  Schield Excel demo.   See Statistical Literacy and Chance

• Five Table survey.  This short survey (~7 minutes) asks respondent which statements accurately describe the circled percentage in five different tables. This survey is available in a web version with immediate grading and feedback on errors, and in a paper version.
• 2008 Statistical Literacy Skills Survey (20 Questions).  This survey was based on the longer 2002 W. M. Keck Statistical Literacy Survey.   For details on the construction of this instrument, see Schield (2008) titled "Statistical Literacy Skills Survey."
• 2002 W. M. Keck Statistical Literacy Survey.  This very long survey (~50 minutes) is available in Perseus-powered web version that acquires the data but gives no interactive feedback, and in a paper version. The results and analysis of this survey are also available.

• Confound Those Speculative Statistics by Schield (2009). ASA  6up
• Presenting Confounding Graphically Using Standardization by Schield (2006). Stats magazine
• Three Graphs to Promote Statistical Literacy by Schield (2004), ICME.
• Frequency of Simpson's Paradox in NAEP Data by Terwilliger and Schield (2004), AERA.
• Simpson's Paradox and Cornfield's Conditions by Schield (1999), ASA JSM.
• Definitions of Confounding

Here are two web-based interactive Excel programs that demonstrate standardization.

• Standardizing for Percentage Outcomes between 0% and 8%.

• Standardizing for Average Outcomes between 0 and 800.

For a broader mathematical background on Simpson's paradox, see

• Exploring Simpson's Paradox by Larry Lesser NCTM 2001

• Version 10: Fall 2012.    [Much improved!]  Student attitudes:  Spring 2013
  Challenges:  2015 Spring
  • Odyssey: A Journey to Lifelong Statistical Literacy by Schield, ICOTS 2014.
  • User Guide (Students) 2013:  Slides
  • User Guide (Students) 2010:  6up   1up and audio-script.
  • System Guide2  (Instructors) 2012:  6up   1up. 
  • System Guide2 (Instructors v3) 2020: Slides
     
• Version 7: 2010 thru summer 2012
  • Guide1-Startup:  slides 6up,   slides 1up,  audio (mp3) and audio-script.
  • Guide2-Play:  slides 6up,  slides 1up, audio (mp3) and audio-script.
  • Schield (2011). Teaching Statistical Literacy using Odyssey2Sense (TM): A Unique Web-Forum MAA. 6up  
  • Schield-Copes Odysseys Poster  2011 Augsburg College

7. USING EXCEL TO PRESENT AND CREATE SUMMARY STATISTICS

Presentation:: Describe and Summarize

• XL0Z: Moodle Split Screen: Excel vs. URL.  Slides.
• XL1A: Use 1D nominal frequency data to create pie & bar count & percent charts:  Output     Slides (12)   Data Input
• XL1B: Use 2D count data to create pie & bar charts:    Count (2C):   Output   Slides (10)  Input      Count & %: Output   Input
• XL1B2: Use ordinal pivot-table data to create pie & bar count & percent charts:  Output     Slides   Input
• XL1C: Create time-based line graphs. Linear and Log-Ratio display.    Output    Slides (12)   Data

Creation of statistical summary data:

• XL1D: Create Pivot tables of counts, averages, statistics and percentages (100% column, 100% row and half table of percentages) 
      Excel 2013  Output    Slides (24)    Data.         Excel 2008 Output   Slides   Data.    Excel 2003 Demo slides: 1up  6up
• XL1E: Create Ranks and Percentiles.   Output    Input
• XL1F:  Create Histogram using Excel HISTOGRAM command:  Excel 2013  Output   Slides (13)   Data    Data (pdf) X
• XL1G: Create Histogram using COUNTIF and FREQUENCY functions:  Excel 2013:  Output   Slides (18)   Data (xlsx)  Data (pdf)
• XL1H: Creating Funnel Charts using Excel 2013: In-cell, stacked bar and stacked area.   Demo   Data
• XL1J: Create centered stacked 100% bar-charts for ordinal data using Excel 2013.    Even and Odd #: Output
             Even #:  Output  Slides  Data                 Odd #:  Output   Slides  Data
• XL1K: Using CORREL function  Output,  Slides  Data
• XL1L:  Interpreting zero correlation.  Output,  Slides,  Data.

8.  MODEL DATA USING EXCEL LINEAR REGRESSION     Pulse dataset

• XL2A: Chart Trendline: Linear  1Y1X (3 graphs)   Demo  Slides (23) 
• XL2B: Chart Trendline: Non-Linear   1Y1X    (6 graphs) Demo   Slides (12)  
• XL2C: Chart Trendline: Linear  Two different Y scales on same graph.  2Y1X (4 graphs)  Demo   Slides (36)
• XL2D: Chart Trendline: Linear  Three-factor 1Y/2Groups/1X.  New (pivot table, 2 graphs):   Demo   Slides (12)   [[Do XL2C first]
• XL2G: Association vs. Causation.  Explains vs. Causes using Excel.  Output
   
•  Linear regression using functions:   Can do on Mac.  
  XL2I:   OLS1A  Weight|Height.    Demo   Slides (12)   Data.     Using Intercept, Slope and R-sq.
  XL2J:   OLS1A  Weight|Height.    Demo   Slides (12)   Data.     Using Predict, Trend and R-sq..
  XL2K:  OLS1A  Weight|Height.   OLS1B  Weight|Ht+Male.   OLS1C  Weight|Height+Rest Pulse.    Demo  Slides (12)  Data.  Using LINEST.
  XL2M:  OLS1A  Weight|Height.  Demo  Slides (12)  Data.   Prediction Intervals using LINEST function
  XL2N:  OLS                                      Demo  Slides (12)  Data.   Non-linear Regression using LINEST.
  XL2O:  OLS1D  Simpson's Reversal Demo  Slides (12)  Data
  --------------------------------------------------------------------------------------------
• Changed names: 3a Wt vs Ht; 3b Wt vs Ht & smoke;  3c Wt vs Ht & Pulse1 (1/18/2018)
  Multiple Regression using Data Analysis Toolpak:
• XL3A: Toolpak: Regression using Data Analysis 1Y1C  Output    Slides (12)    Input      Weight by Height
• XL3B: Toolpak: Regression using Data Analysis 1Y2BC  Output   Slides (18)   Input      Weight by Height and Gender
• XL3C: Toolpak: Regression using Data Analysis 1Y2C    Output   Input     [No slides]   Weight by Height and Pulse1
• XL3D: Toolpak: Regression MV4   Example of Simpson's Paradox.  Output   Slides   Data
• XL3E: Toolpak: Regression MV5 Assess data.  Explain multivariate regression as standardizing.  Demo    Data
• XL3F: Segmented OLS Linear Regression:    Slides (13)        Math vs. Statistics NNN (2016 draft)
• XL3G: Toolpak Regression: Key Bivariate OLS Relationships    Output    S1: SE of regression; 1-R^2.  S2: CI and PI.
• XL3M: Modelling using simple reasoning.  Summarizing/Modelling Production of CO2 gases by County.  XLSX

9.  MODEL DATA USING EXCEL LOGISTIC REGRESSION:

• Logistic Regression using OLS1: Nudged probabilities.  Handles multiple X.  Accuracy better than linear OLS; less than logit MLE.
  XL4A  OLS1A Male|Ht  Demo  Slides (12)  Data.        XL4B OLS1B  Male|Ht+Smoker  Demo  Slides (12)  Data.
  XL4C  OLS1C Male|Wt  Demo  Slides (12)  Data .       XL4D OLS1D  Male|Ht+Wt         Demo  Slides (18)  Data
  XL4E  OLS1E Outcome | Predictor + Confounder.  Results in a Simpson's Reversal  Output   Data
  
  XL4F  Run logistic demo given a underlying coefficients. Sheet 1C: Single continuous predictor. Sheet 2CB: One continuous and one binary.
  XL4G Run logistic demo given X50 and slope. Sheet 1C: single continuous predictor .   Sheet 2CB: One continuous and one binary
   
• Logistic Regression:  MLE using Excel Solver
  XL4K: 1Y1X-Ht  2 steps MLE1A:  Demo   Slides (22)   Input.    3 steps: Demo  Slides (22)  Input.    
  XL4L: (1Y2X).     3 steps MLE1C:  Demo   Slides (18)   Input
   Analysis using SPSS  Howell   More 2      Minitab Binary Logistic Regression  Forecast Carrying Capacity
• XL4M Logistic Regression using MLE: Simpson's Paradox
• XL4N Discriminant Analysis using MLE Logistic Regression:  Demo    Pulse 1Y2X.  Using OLS1D: Slides (18)
   
• XL4P Construct Model of World CO2 Carbon Emissions from Fuel Combustion  Data
• XL4S  Logistic Regression using OLS2: Grouped data.  Chart Trendline 1Y1X    Data Analysis 1Y2X     Log-odds-Grouped Data OLS
• XL4T Logistic Regression using OLS3 shortcut.   Output    [Slides missing]  Input    [Interesting but can't handle multiple X]
• XL4U Logistic Regression: Compare MLE with OLS1.  Slides (16)  Demo    Data (xlsx)  [Handles multiple X] 
• XL4V Logistic Regression: Compare MLE with OLS3.  Slides (18)    Data (xlsx)  [Interesting but can't handle multiple X] 
   
• R^2 and Partial Correlation as a function of Added Variable Correlations.  (1/22/2017)

10.  DISCRETE DISTRIBUTIONS USING EXCEL:

• XL1P: Create Binomial, Hypergeometric and Poisson Distributions using Excel.   Discrete Probabilities: Overview   
        Output (pdf)   Slides (10)    Input    
• XL1Q: Explore Binomial, Hypergeometric and Poisson Distribution PDF and CDF for statistical significance.
       #Excel 2013:   Slides       Demo Output (pdf)    PDF & CDF Calculator Input
• XL1R: Calculator for three discrete distributions:   Excel file

11.  CONTINUOUS DISTRIBUTIONS USING EXCEL:  

• Lognormal Distribution of HH by Income given Mean and Median of distribution:  
  XL5A using Excel 2013:   Demo Output     Slides (6)    Demo Input (xlsx).
   
• Distribution of Total Income assuming HH by income are log-normal (Excel 2013)  Irfan (2014)   Schield-Income-Inequality
  Explore Income #1:  Spreadsheet#1      NNN slides (24)    Updated slides (18)
  Explore Income #2:  Spreadsheet#2      Results         Spreadsheet#3
  XL5B  LogNormal Income2  Demo4Output   Demo6  Slides (12)    Input.
   
• XL5C LogNormal Income Demo:   XLSX by Percentiles  Protected. Input Mean and Median.
• XL5C1  LogNormal Income Demo: Demo2   Demo4  Demo5    Input.   Schield (2014)
   
• XL5D  Log-Normal Distribution of Subjects by Value: Percentages only. Spreadsheet
• XL5D1  Log-Normal Distribution of Households by Assets (Excel 2013)   Spreadsheet.  Slides
• XL5D2  Log-Normal Distribution of  (Excel 2013)   Spreadsheet.  Slides
• XL5D3  Log-Normal characteristics as a function of Mean-Median ratio: Spreadsheet   PDF
• XL5D9  Log-Normal Distribution of VIX (Excel 2013)   Spreadsheet.  Slides
   
• XL5E Generating Mean or Median of Log-Normal distribution given Standard Deviation.  PDF
• XL5F  Generate Distribution of Losses given Lognormal Distributions of Frequency and Severity [Old] Demo  Slides  Data   Demo-SS
• XL5F  Run Demo to Generate Distribution of Losses given Lognormal Distributions of Frequency and Severity   Demo XLSX    Demo PDF 
• XL5H Distribution of Product of Two Random Variables: Normal and Log-Normal (Excel Simulation).  Output. 
   
• XL5S   Normal Distribution and CDF (Excel 2013)   Spreadsheet.  Slides
• XL5T   Folded-Normal Distribution and CDF
• XL5U   Exponential Distribution and CDF
• XL5V  Chi-squared Distribution and CDF
   

12. CREATE DISTRIBUTIONS EMPIRICALLY FROM RANDOM PROCESSES USING EXCEL    NNN 2014: Slides (pdf)  PPT

• XL6A: Compare Mean and Median from Uniform and Normal.   V1: 20 or 80 groups; 10 each (xlsx).

• XL6B: Normal distribution from the Sum of Random Variables:   Discrete,  Uniform, and Normal   (xlsx)

• XL6C: Lognormal distribution from the product of Positive Variables:  Normal (xlsx)

• XL6D: Exponential decay as result of random deaths (xlsx)

• XL6E: Chi-square distribution from the random assignment to cells in table.  DF=3 (xlsx)

• XL6F: Excel: Chi-squared functions in Excel2013.

• XL6G: Matching groups from random assignment

13. SAMPLE STATISTICS FOR PERFECTLY REPRESENTATIVE SAMPLES:

• XL7K: Extreme values for samples from Normal distributions  2013
• XL7L: Kurtosis in Representative Samples from Normal distributions as a function of sample size.  8/2016   Excel

14. CREATE SAMPLING DISTRIBUTIONS USING EXCEL:

• XL7A: Create sampling distributions for a single die using COUNTIF (n=4, 16, 25, 50, 200).   Output  Slides  Data
• XL7B: Create sampling distributions of the mean (n=16) for coin, die, normal, exponential and log-normal.
• XL7C: Show sampling variability of mean is less than that of median (xlsx)
• XL7D: Create sampling distribution of skewness from a Normal (N=10).
• XL7E: Show Standard Deviation of sample means is less for stratified random than for simple random.   Demo
• Averaging Log-Normal Losses as a function of sample size

15. CREATE AND COMPARE CONFIDENCE INTERVALS USING EXCEL:

• XL8A: Create Confidence Intervals using Excel 2013:  Results, Slides (12), Data.     Excel 2010: Demo, Slides (12), Data.
• XL8B: Compare overlap of Two Confidence Intervals using Excel 2010.  PDF    xlsx
• XL8C: Display Paired Confidence Intervals using Excel with summary statistics. Template (xls).     Demo: 6up, 1up.
• XL8J Reference: Compare confidence functions in Excel 2010 vs. Excel 2003.   PDF   xlsx.
• XL8K Reference: Compare Z and T Statistics using Excel 2003.    PDF

16. CREATE HYPOTHESIS TESTS USING EXCEL:

Isaacson data set (240 rows, 8 columns).

• XL9A: Hypothesis test for a single Population: Z-Test function.   Excel 2008 demo:   Slides (12) 6up and 1up.
• XL9B: Hypothesis test (two populations):  T-Test function.     Excel 2008  Demo Slides (24)  6up, 1up.
• XL9C: Hypothesis test (two populations):  T-Test command.  Excel 2013 Slides (19)  6up, 1up.  Excel 2003 6up, 1up.

17. APPROXIMATE CUTOFFS FOR STATISTICAL SIGNIFICANCE: Sufficient but not necessary.  

• Slides from Feb 25 StatChat:  Slides
• XL9D: Modelling Statistically-Significant Success for Bernoulli Distribution.   Schield (2017)   Demo
• XL9E: Modelling Statistically-Significant Chi-squared:  Chi^2 > 2*(DF+1).   Schield (2014).
• XL9F: Model Statistically-Significant Skewness when sampling from a Normal.  N<100.  N<500
• XL9G: Modelling Statistically-Significant Correlation: r > 2/Sqrt(n).  Slides  PDF   Excel worksheet.  Schield (2013)
• XL9H: Modelling Statistically-Significant T-statistic (ssT):  For one and two-tailed.  Schield (2015).
• XL9J: Relative Risk Cutoffs for Statistical-Significance Schield (2014).   Relative Risk Calculator (xlsx)
• XL9K: Compare RR with Proportions Difference for Statistical Significance (Worksheet).

18. USING MICROSOFT WORD:

• 20 Minute Quick Start using Word 2013 Styles. Slides (pdf).   Schield, May 2014.

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