GeoGebra Apps for A-Level Statistics

Mark Willis, Aug 24, 2020

Table of Contents

  1. Data processing, presentation and interpretation
    1. Drawing a frequency diagram from grouped data.
    2. Distributions and skewness
    3. Covariance
    4. Histogram of heights from large data set
    5. Linear interpolation
    6. Histograms, box plots and statistics
    7. Stem and leaf plots, box plots and outliers
    8. Skewness of a probability distribution
  2. The binomial distribution.
    1. Binomial distribution probability calculator
    2. Approximating a binomial distributionby a normal distribution.
    3. Binomial & inverse binomial probability calculator
  3. The poisson distribution
    1. Approximating a Poisson distribution by a normal distribution.
  4. The normal distribution
    1. Normal & InverseNorm calculator
    2. The normal distribution.
    3. Inverse normal probability calculator
    4. The normal distribution
    5. Normal distribution probability calculator
    6. Coding using the normal distribution
  5. Statistical hypothesis testing
    1. The distribution of the sample mean
    2. Central limit theorem for samples from a binomial dist
    3. Central limit theorem for samples from a Poisson dist
    4. Covariance and correlation introduction.
  6. Continuous random variables
    1. Modelling students arriving late using a probability density function.
    2. A continuous probability density function.
    3. A probability density function.
    4. A continuous variable probability function.
    5. Using the cumulative distribution function to find probabilities.
    6. Continuous probability density function.
    7. Continuous probability density function.
    8. Finding the mode of a probability density function.
    9. t-distribution calculator
    10. Chi-Squared distribution calculator
  7. Continuous uniform/rectangular distribution
    1. Continuous uniform/rectangular distribution.
    2. Continuous uniform distribution finding probabilities.
    3. Cumulative distribution function for continuous uniform distribution.
  8. Other discrete distributions
    1. Poisson distribution calculator
    2. Hypergeometric distribution calculator
    3. Negative Binomial distribution
    4. Geometric distribution probability calculator

1.

Data processing, presentation and interpretation

  • 1. Drawing a frequency diagram from grouped data.
  • 2. Distributions and skewness
  • 3. Covariance
  • 4. Histogram of heights from large data set
  • 5. Linear interpolation
  • 6. Histograms, box plots and statistics
  • 7. Stem and leaf plots, box plots and outliers
  • 8. Skewness of a probability distribution

1.1.

Drawing a frequency diagram from grouped data.

– Mark Willis

1.2.

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1.3.

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1.4.

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1.5.

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1.6.

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1.7.

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1.8.

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2.

The binomial distribution.

  • 1. Binomial distribution probability calculator
  • 2. Approximating a binomial distributionby a normal distribution.
  • 3. Binomial & inverse binomial probability calculator

2.1.

Binomial distribution probability calculator

– Mark Willis

2.2.

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2.3.

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3.

The poisson distribution

  • 1. Approximating a Poisson distribution by a normal distribution.

3.1.

Approximating a Poisson distribution by a normal distribution.

– Mark Willis

4.

The normal distribution

  • 1. Normal & InverseNorm calculator
  • 2. The normal distribution.
  • 3. Inverse normal probability calculator
  • 4. The normal distribution
  • 5. Normal distribution probability calculator
  • 6. Coding using the normal distribution

4.1.

Normal & InverseNorm calculator

– Mark Willis

4.2.

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4.3.

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4.4.

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4.5.

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4.6.

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5.

Statistical hypothesis testing

  • 1. The distribution of the sample mean
  • 2. Central limit theorem for samples from a binomial dist
  • 3. Central limit theorem for samples from a Poisson dist
  • 4. Covariance and correlation introduction.

5.1.

The distribution of the sample mean

[b]1.[/b] Move the slider to change the sample size [i]n[/i].[br][b]2.[/b] Click to see distributions of the sample mean.
– Mark Willis

5.2.

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5.3.

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5.4.

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6.

Continuous random variables

  • 1. Modelling students arriving late using a probability density function.
  • 2. A continuous probability density function.
  • 3. A probability density function.
  • 4. A continuous variable probability function.
  • 5. Using the cumulative distribution function to find probabilities.
  • 6. Continuous probability density function.
  • 7. Continuous probability density function.
  • 8. Finding the mode of a probability density function.
  • 9. t-distribution calculator
  • 10. Chi-Squared distribution calculator

6.1.

Modelling students arriving late using a probability density function.

– Mark Willis

6.2.

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6.3.

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6.4.

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6.5.

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6.6.

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6.7.

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6.8.

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6.9.

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6.10.

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7.

Continuous uniform/rectangular distribution

  • 1. Continuous uniform/rectangular distribution.
  • 2. Continuous uniform distribution finding probabilities.
  • 3. Cumulative distribution function for continuous uniform distribution.

7.1.

Continuous uniform/rectangular distribution.

– Mark Willis

7.2.

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7.3.

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8.

Other discrete distributions

  • 1. Poisson distribution calculator
  • 2. Hypergeometric distribution calculator
  • 3. Negative Binomial distribution
  • 4. Geometric distribution probability calculator

8.1.

Poisson distribution calculator

– Mark Willis

8.2.

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8.3.

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8.4.

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