StatLit Tools
11/30/22

Authors Popular StatLit News Authors-Academic Statistical Literacy Numeracy Statistical Reasoning

StatLit Papers Schield Publications Standardizing StatLit Videos StatLit TextBook StatLit Tools US-ISLP StatLitSite David & Phyllis Whitin

This page contains various tools that may be helpful.  All these tools are web-accessible and are freely available for use.    Tom Burnham (pictured above) created the VB tools (Reading/Writing drill); Milo Schield created the Excel demonstrations and documentation.   Burnham accomplishments
  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


0. BASICS/TOOLS:

1. CHANCE-COINCIDENCE DEMONSTRATIONS:


2. SURVEYS:
This web site contains several surveys along with results from various groups.
  • 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.

3. DESCRIBE AND COMPARE PERCENTAGES, RATES AND AVERAGES USING ORDINARY ENGLISH:
    
Isaacson data set (240 rows, 8 columns).


4. STANDARDIZING:
Standardizing is a new graphical technique for taking into account the influence of a related factor. 
This site contains several articles on confounding, standardization and Simpson's Paradox.

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

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


5. RATIO GRAMMAR READING-WRITING DRILLS:   Tom Burnham Accomplishments (1995-2014)
Go to the Grammar Read-Write Index page for details on browser choice, compatibility mode, and for various demos (video, PowerPoint w audio and PowerPoint slides).

6. ODYSSEYS2SENSE: a game of lively discourse.    Website:

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

  • XL6G: Matching groups from random assignment


13. SAMPLE STATISTICS FOR PERFECTLY REPRESENTATIVE SAMPLES:


14. CREATE SAMPLING DISTRIBUTIONS USING EXCEL:


15. CREATE AND COMPARE CONFIDENCE INTERVALS USING EXCEL:

  • XL8A: Create Confidence Intervals using Excel 2013:  Results, Slides (12), Data.     Excel 2010: DemoSlides (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.  



18. USING MICROSOFT WORD:

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

MISCELLANEOUS:
To print the SQL statements in a MS Access query, checkout Print Access Query SQL.

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This site was last updated 11/30/22