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Data

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Sample

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Statistics

Graphs

Descriptive Statistics
Graphs

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* Note: Quartiles are calculated by excluding the median on both sides.

Sample Mean

Sample Standard Deviation

Boxplot

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Histogram

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Stem and Leaf Plot

* Note: Outlier values are listed under the HI/LO lists.

Distribution

Contingency Table

Binomial

Poisson

Hypergeometric

Negative Binomial

Normal

Dimension

2 x 2 2 x 3 3 x 2 3 x 3

Probabilities

Marginal Joint Union Conditional

Number of Trials (\( n\))

Probability of Success (\( p\))

Probability

\(P(X = x \))

\(P(X \leq x)\)

\(P(X \ge x)\)

\(P(X \gt x)\)

\(P(X < x)\)

\(P(x_1 \leq X \leq x_2)\)

Number of Successes (\( x\))

Number of Successes (\( x_{1}\))

Number of Successes (\( x_{2}\))

Options

Display Probability Distribution Table

Average (\( \mu\))

Probability

\(P(X = x \))

\(P(X \leq x)\)

\(P(X \ge x)\)

\(P(X \gt x)\)

\(P(X < x)\)

\(P(x_1 \leq X \leq x_2)\)

Number of Successes (\( x\))

Number of Successes (\( x_{1}\))

Number of Successes (\( x_{2}\))

Options

Display Probability Distribution Table

Population Size (\( N\))

Number of Successes in the Population (\( M\))

Sample Size (\( n\))

Probability

\(P(X = x \))

\(P(X \leq x)\)

\(P(X \ge x)\)

\(P(X \gt x)\)

\(P(X < x)\)

\(P(x_1 \leq X \leq x_2)\)

Number of Successes in the Sample (\( x\))

Number of Successes in the Sample (\( x_{1}\))

Number of Successes in the Sample (\( x_{2}\))

Options

Display Probability Distribution Table

Number of Successes (\( r\))

Probability of Successes (\( p\))

Probability

\(P(X = x \))

\(P(x_1 \leq X \leq x_2)\)

Trials

Failures prior to the \(r^{th}\) success Trials until (and including) the \(r^{th}\) success

Number of Failures prior to the \(r^{th}\) success (\( x\))

Trials until (and including) the \(r^{th}\) success (\( x\))

Population Mean (\( \mu\))

Population Standard Deviation (\( \sigma\))

Type of Calculation

Probability Quantile

Sampling Distribution of the Sample Mean

Probability

\(P(X \leq x)\) or \(P(X < x)\)

\(P(X \ge x)\) or \(P(X \gt x)\)

\(P(x_1 \leq X \leq x_2)\)

Normally Distributed Variable (\( x\))

Normally Distributed Variable (\( x_{1}\))

Normally Distributed Variable (\( x_{2}\))

Probability

\(P(\bar{X} \leq x)\) or \(P(\bar{X} < x)\)

\(P(\bar{X} \ge x)\) or \(P(\bar{X} \gt x)\)

\(P(x_1 \leq \bar{X} \leq x_2)\)

Normally Distributed Variable (\( \bar{x}\))

Normally Distributed Variable (\( \bar{x}_{1}\))

Normally Distributed Variable (\( \bar{x}_{2}\))

Sample Size (\( n\))

Quartiles \( (Q_{1}, Q_{2}, Q_{3}) \) Percentile

Percentile Value

Parameter of Interest

Population Mean (\( \mu \)) Population Proportion (\( p\))

Confidence Level (\( 1- \alpha\))

90% 95% 99%

Estimation Type

Margin of Error (\( E\)) Width of Interval (\( W\))

Population Standard Deviation (\( \sigma\))

Margin of Error (\( E\))

Width of Interval (\( W\))

Target Proportion (\( \hat{p} \))

Margin of Error (\( E\))

Width of Interval (\( W\))

Sample Size Estimate (\( n \))

Methodology

Inference about 1 sample\(\)

Inference about 2 samples\(\)

Inference about more than 2 samples (e.g. ANOVA)\(\)

Inference for Categorical Data (e.g \( \chi^2 \) test)

Parameter of Interest

Population Mean (\( \mu \))

Population Standard Deviation (\( \sigma\))

Population Proportion (\( p\))

Data Availability

Summarized Data Enter Raw Data Upload Data

Sample Size (\( n\))

Sample Mean (\( \bar{x}\))

Is Population Standard Deviation (\( \sigma\)) known?

Known Unknown

Population Standard Deviation (\( \sigma\)) Value

Sample Standard Deviation (\( s\)) Value

Sample

Population Standard Deviation (\( \sigma\))

Known Unknown

Population Standard Deviation (\( \sigma\)) Value

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Population Standard Deviation (\( \sigma\))

Known Unknown

Population Standard Deviation (\( \sigma\)) Value

Number of Successes (\( x\))

Number of Trials (\( n\))

Sample Size (\( n\))

Sample Standard Deviation (\( s\))

Inference Type

Confidence Interval Hypothesis Testing

Confidence Level (\( 1- \alpha\))

90% 95% 99%

Significance Level (\( \alpha\))

10% 5% 1%

Hypothesized Population Mean (\( \mu_{0}\)) Value

Hypothesized Population Proportion (\( p_{0}\)) Value

Hypothesized Population Standard Deviation (\( \sigma_{0}\)) Value

Alternate Hypothesis (\( H_{a}\))

Graph Options

Boxplot for Sample Data

Parameter of Interest

Two Independent Populations (\( \mu_{1} - \mu_{2} \))

Dependent (Paired) Populations (\( \mu_{d} \))

Two Population Proportions (\( p_{1} - p_{2}\))

Data Availability

Summarized Data Enter Raw Data Upload Data

Sample Size 1 (\( n_{1}\))

Sample Mean 1 (\( \bar{x}_{1}\))

Sample Size 2 (\( n_{2}\))

Sample Mean 2 (\( \bar{x}_{2}\))

Are Population Standard Deviations (\( \sigma_{1}\) and \( \sigma_{2}\)) known?

Both Known Both Unknown

Population Standard Deviation 1 (\( \sigma_{1}\)) Value

Population Standard Deviation 2 (\( \sigma_{2}\)) Value

Assume Population Variances are equal (\( \sigma_{1}^2\) = \( \sigma_{2}^2\))?

Yes (Pooled) No (Welch-Satterthwaite df)

Sample Standard Deviation 1 (\( s_{1}\)) Value

Sample Standard Deviation 2 (\( s_{2}\)) Value

Sample 1

Sample 2

Are Population Standard Deviations (\( \sigma_{1}\) and \( \sigma_{2}\)) known?

Both Known Both Unknown

Assume Population Variances are equal (\( \sigma_{1}^2\) = \( \sigma_{2}^2\))?

Yes (Pooled) No (Welch-Satterthwaite df)

Population Standard Deviation 1 (\( \sigma_{1}\)) Value

Population Standard Deviation 2 (\( \sigma_{2}\)) Value

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Choose a Column for Sample 1

Choose a Column for Sample 2

Are Population Standard Deviations (\( \sigma_{1}\) and \( \sigma_{2}\)) known?

Both Known Both Unknown

Assume Population Variances are equal (\( \sigma_{1}^2\) = \( \sigma_{2}^2\))?

Yes (Pooled) No (Welch-Satterthwaite df)

Population Standard Deviation 1 (\( \sigma_{1}\)) Value

Population Standard Deviation 2 (\( \sigma_{2}\)) Value

Data Availability

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Before

After

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Choose a Column for 'After' Sample Data

Number of Successes 1 (\( x_{1}\))

Number of Trials 1 (\( n_{1}\))

Number of Successes 2 (\( x_{2}\))

Number of Trials 2 (\( n_{2}\))

Inference Type

Confidence Interval Hypothesis Testing

Confidence Level (\( 1- \alpha\))

90% 95% 99%

Significance Level (\( \alpha\))

10% 5% 1%

Alternate Hypothesis (\( H_{a}\))

Graph Options

Side-by-side Boxplot for Sample Data

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Data Format

Values in multiple columns

Responses and factors stacked in two columns

Choose columns to conduct analysis

Response Variable

Factors

Significance Level (\( \alpha\))

10% 5% 1%

Options

Include post hoc tests

Graphs

Dimension

2 x 2 2 x 3 3 x 2 3 x 3

Name for Row Variable (optional):

Name for Column Variable (optional):

Hypothesis Test

Chi-Square test for independence Fisher's Exact test

with Yates continuity correction

Significance Level (\( \alpha\))

10% 5% 1%

Confidence Interval

Hypothesis Test

Boxplot

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Confidence Interval

Hypothesis Test

Confidence Interval

Hypothesis Test

Confidence Interval

Hypothesis Test

Boxplot

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Confidence Interval

Hypothesis Test

Data

Confidence Interval

Hypothesis Test

Analysis
Graphs
Uploaded Data

One-way Analysis of Variance (ANOVA)

Side-by-side Boxplot

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Histogram of Residuals

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QQ Plot of Residuals

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Group Means

Plot Options

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Chi-Square Test for Independence

Observed Frequencies

Expected Frequencies

Calculation of the \( \chi^2 \) statistic value

Fisher's Exact Test

Observed Frequencies

Hypothesis Test

Regression Type

Simple Linear Regression and Correlation Analysis

Data

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\( x\) (Independent Variable)

\( y\) (Dependent Variable)

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Choose the Explanatory Variable (x)

Choose the Response Variable (y)

Graph Options

Scatterplot of \( x\) versus \( y\)

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Choose the Explanatory Variables (x1, x2, x3, ...)

Choose the Response Variable (y)

Simple Linear Regression
Correlation Analysis
Uploaded Data

Scatterplot

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Plot Points Colour

Line Width

Point Size

Funding Agency / Coursework	Recipient	Date(s)
Provost’s Teaching and Learning Enhancement Grant (TLEG)	Bryce Carson	November 2024 through January 2025
Provost’s Teaching and Learning Enhancement Grant (TLEG)	Michael Myer	September 2023 through April 2024
Faculty of Science and Technology (FST) Student Research Award	Michael Myer	June through August 2023
COMP 5690: Senior Computer Science Project	Crystal Wai	September through December 2022

Sample Mean

Sample Standard Deviation

Boxplot

Plot Options

Boxplot Options

Histogram

Plot Options

Stem and Leaf Plot

Sample Size Estimate (\( n \))

Sample Size Estimate (\( n \))

Confidence Interval

Hypothesis Test

Boxplot

Plot Options

Boxplot Options

Confidence Interval

Hypothesis Test

Confidence Interval

Hypothesis Test

Confidence Interval

Hypothesis Test

Boxplot

Plot Options

Boxplot Options

Confidence Interval

Hypothesis Test

Data

Confidence Interval

Hypothesis Test

One-way Analysis of Variance (ANOVA)

Side-by-side Boxplot

Plot Options

Boxplot Options

Histogram of Residuals

Plot Options

QQ Plot of Residuals

Plot Options

Group Means

Plot Options

Chi-Square Test for Independence

Observed Frequencies

Expected Frequencies

Calculation of the \( \chi^2 \) statistic value

Fisher's Exact Test

Observed Frequencies

Hypothesis Test

Scatterplot

Plot Options

Scatterplot Options

Data

Estimated equation of the regression line

Pearson's Product-Moment Correlation

Kendall's Rank Correlation

Spearman's Rank Correlation

Data File

Developers

Project Supervisor

Current project members

Past project members

Acknowledgements

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