Hypothesis Testing Calculators

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The Joy of a Teacher is the Success of his Students. - Samuel Dominic Chukwuemeka B.Eng., A.A.T, M.Ed., M.S


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First: read the notes. Second: review the formulas and the tables. Third: view the videos. Fourth: solve the questions/solved examples. Fifth: check your solutions with my thoroughly-explained solutions. Sixth: check your answers with the calculators as applicable.

I wrote most of the codes for these calculators using Javascript, a client-side scripting language. Please use the latest Internet browsers. The calculators should work. Comments, ideas, areas of improvement, questions, and constructive criticisms are welcome. Should you need to contact me, please use the form at the bottom of the page. If you are my student, please do not contact me here. Contact me via the school's system. Thank you for visiting.

Samuel Dominic Chukwuemeka (SamDom For Peace) B.Eng., A.A.T, M.Ed., M.S

Samdom For Peace

Population Proportion



Goodness-of-Fit Test

(One-Way Frequency Table)

Contingency Table

(Two-Way Frequency Table)

Test of Independence

Fisher Exact Test: Test of Homogeneity

McNemar's Test: Test for Matched Pairs


Population Standard Deviation


Population Mean



One-Way ANOVA

(The Completely Randomized Design)

Two-Way ANOVA

(The Factorial Design)


Correlation and Regression


Population Variance


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x

One Sample Proportion: Left-Tailed

Given: CL

To Find: α, -zα/2

in

Given: α

To Find: CL, -zα/2

in

Given: p, p̂, α

Test hypothesis using Classical Approach and P-value Approach

in

in

in

Given: p, n, x, α

Test hypothesis using Classical Approach and P-value Approach

in

in

Given: p, n, x of a Binomial Distribution; α

Test hypothesis using P-value Approach

in

in

x

One Sample Proportion: Right-Tailed

Given: CL

To Find: α, zα

in

Given: α

To Find: CL, zα

in

Given: p, p̂, α

Test hypothesis using Classical Approach and P-value Approach

in

in

in

Given: p, n, x, α

Test hypothesis using the Classical Approach and P-value Approach

in

in

Given: p, n, x of a Binomial Distribution; α

Test hypothesis using P-value Approach

in

in

x

One Sample Proportion: Two Tails

Given: σ, x, n, p

Test hypothesis using the Classical Approach and the P-value Approach

in

in

Given: p, p̂, α

Test hypothesis using Classical Approach and P-value Approach

in

in

in

Given: CL, x, n, p

Test hypothesis using the Confidence Interval Method

in

in

Given: p, n, x of a Binomial Distribution; α

Test hypothesis using P-value Approach

in

in

x

Two Samples Proportion: Left-Tailed

Given: x1, n1, x2, n2, α

Test hypothesis using Classical Approach and P-value Approach

in

x

Two Samples Proportion: Right-Tailed

Given: x1, n1, x2, n2, α

Test hypothesis using Classical Approach and P-value Approach

in

x

Two Samples Proportion: Two-Tailed

Given: σ, x, n, p

Test hypothesis using the Classical Approach and the P-value Approach

in

Two Samples Proportion: Confidence Interval Estimate

Given: x1, n1, x2, n2, α

To: Construct a confidence interval for p1 - p2

in

x

One Sample Mean: Left-Tailed

Given: CL, df

To Find: α, critical t

in

Given: α, df

To Find: CL, critical t

in

Given: CL, n

To Find: α, critical t

in

Given: α, n

To Find: CL, critical t

in

Given: Raw dataset x (from Sample)

To calculate: sample size, mean, standard deviation

Given: sample size, test statistic

To calculate: degrees of freedom, P-value

Given: μ, x̄, s, n, α

Test hypothesis using Classical Approach and P-value Approach

in

Given: μ, x̄, σ, n, α

Test hypothesis using Classical Approach and P-value Approach

in

x

One Sample Mean: Right-Tailed

Given: CL, df

To Find: α, critical t

in

Given: α, df

To Find: CL, critical t

in

Given: CL, n

To Find: α, critical t

in

Given: α, n

To Find: CL, critical t

in

Given: Raw dataset x (from Sample)

To calculate: sample size, mean, standard deviation

Given: sample size, test statistic

To calculate: degrees of freedom, P-value

Given: μ, x̄, s, n, α

Test hypothesis using Classical Approach and P-value Approach

in

Given: μ, x̄, σ, n, α

Test hypothesis using Classical Approach and P-value Approach

in

x

One Sample Mean: Two-Tailed

Given: CL, df

To Find: α, critical t

in

Given: α, df

To Find: CL, critical t

in

Given: CL, n

To Find: α, critical t

in

Given: α, n

To Find: CL, critical t

in

Given: Raw dataset x (from Sample)

To calculate: sample size, mean, standard deviation

Given: sample size, test statistic

To calculate: degrees of freedom, P-value

Given: μ, x̄, s, n, α

Test hypothesis using Classical Approach and P-value Approach

in

Given: μ, x̄, s, n, CL

Test Hypothesis using the Confidence Interval Method

in

Given: μ, x̄, σ, n, α

Test hypothesis using Classical Approach and P-value Approach

in

x

Two Samples Mean: Left-Tailed

Given: Raw datasets X1 and X2 (Samples)

To calculate: sample sizes, sample means, sample standard deviations, degrees of freedom (several ones - use whatever is applicable)

Use for Independent Samples

Given: Raw datasets X1 and X2 (Samples)

To calculate: differences between values; sample size, sample mean, and sample standard deviation of the difference, degrees of freedom

Use for Dependent Samples

Two Independent Samples

Given: x̄1, x̄2, s1, s2, n1, n2, α

σ1 and σ2 are unknown, and are assumed to be equal.

Pooled Sample Variance is used

Test hypothesis using Classical Approach and P-value Approach

in

Two Independent Samples - Confidence Interval Method

Given: x̄1, x̄2, s1, s2, n1, n2, CL

σ1 and σ2 are unknown, and are not assumed to be equal

Pooled Sample Variance is used

Construct a confidence interval for μ1 - μ2

in

Two Independent Samples

Given: x̄1, x̄2, s1, s2, n1, n2, α

σ1 and σ2 are unknown, and are not assumed to be equal

Test hypothesis using Classical Approach and P-value Approach

in

Two Independent Samples - Confidence Interval Method

Given: x̄1, x̄2, s1, s2, n1, n2, CL

σ1 and σ2 are unknown, and are not assumed to be equal

Construct a confidence interval for μ1 - μ2

in

x

Two Samples Mean: Right-Tailed

Given: Raw datasets X1 and X2 (Samples)

To calculate: sample sizes, sample means, sample standard deviations, degrees of freedom (several ones - use whatever is applicable)

Use for Independent Samples

Given: Raw datasets X1 and X2 (Samples)

To calculate: differences between values; sample size, sample mean, and sample standard deviation of the difference, degrees of freedom

Use for Dependent Samples

Two Independent Samples

Given: x̄1, x̄2, s1, s2, n1, n2, α

σ1 and σ2 are unknown, and are assumed to be equal.

Pooled Sample Variance is used

Test hypothesis using Classical Approach and P-value Approach

in

Two Independent Samples - Confidence Interval Method

Given: x̄1, x̄2, s1, s2, n1, n2, CL

σ1 and σ2 are unknown, and are not assumed to be equal

Pooled Sample Variance is used

Construct a confidence interval for μ1 - μ2

in

Two Independent Samples

Given: x̄1, x̄2, s1, s2, n1, n2, α

σ1 and σ2 are unknown, and are not assumed to be equal

Test hypothesis using Classical Approach and P-value Approach

in

Two Independent Samples - Confidence Interval Method

Given: x̄1, x̄2, s1, s2, n1, n2, CL

σ1 and σ2 are unknown, and are not assumed to be equal

Construct a confidence interval for μ1 - μ2

in

x

Two Samples Mean: Two-Tailed

Given: Raw datasets X1 and X2 (Samples)

To calculate: sample sizes, sample means, sample standard deviations, degrees of freedom (several ones - use whatever is applicable)

Two Independent Samples

Given: x̄1, x̄2, s1, s2, n1, n2, α

σ1 and σ2 are unknown, and are assumed to be equal.

Pooled Sample Variance is used

Test hypothesis using Classical Approach and P-value Approach

in

Two Independent Samples - Confidence Interval Method

Given: x̄1, x̄2, s1, s2, n1, n2, CL

σ1 and σ2 are unknown, and are not assumed to be equal

Pooled Sample Variance is used

Construct a confidence interval for μ1 - μ2

in

Two Independent Samples

Given: x̄1, x̄2, s1, s2, n1, n2, α

σ1 and σ2 are unknown, and are not assumed to be equal

Test hypothesis using Classical Approach and P-value Approach

in

Two Independent Samples - Confidence Interval Method

Given: x̄1, x̄2, s1, s2, n1, n2, CL

σ1 and σ2 are unknown, and are not assumed to be equal

Construct a confidence interval for μ1 - μ2

in

x

Sample Data: Right-Tailed

Given: CL, df

To Find: α, critical Chi-Square

in

Given: α, df

To Find: CL, critical Chi-Square

in

Given: OV, EV

To Find: df, Χ2 (Show all steps), P-value

Given: OV, Probabilities, Total Number of Trials OR Given: Benford's Law

To Find: EV, df, Χ2 (Show all steps), P-value

Given: OV, EV, α (Use 5% if not specified)

Test Hypothesis Using Classical Approach and P-value Approach

in

Given: OV, Probabilities, Total Number of Trials, α (Use 5% if not specified) OR Given: Benford's Law, α (Use 5% if not specified)

Test Hypothesis Using Classical Approach and P-value Approach

in

x

One-Way ANOVA: Three Samples of Equal Sizes

Given: Datasets 1, 2, and 3

Calculate the F test statistic (Show all work)

Given: Datasets 1, 2, and 3

Test Hypothesis Using Classical Approach and P-value Approach

in

x

One Sample Standard Deviation: Left-Tailed

Given: n, s, σ, α

Test hypothesis using Classical Approach and P-value Approach

in

Given: Raw dataset x (from Sample)

To calculate: sample size, sample standard deviation

x

One Sample Standard Deviation: Right-Tailed

Given: n, s, σ, α

Test hypothesis using Classical Approach and P-value Approach

in

Given: Raw dataset x (from Sample)

To calculate: sample size, sample standard deviation

x

One Sample Standard Deviation: Two-Tailed

Given: n, s, σ, α

Test hypothesis using Classical Approach and P-value Approach

in

Given: n, s, σ, CL

Test Hypothesis using the Confidence Interval Method

in

Given: Raw dataset x (from Sample)

To calculate: sample size, sample standard deviation

x

Two Samples Correlation: Left-Tailed

Given: datasets X and Y

Test hypothesis using the Critical Value Method and the P-value Method

in

x

Two Samples Correlation: Right-Tailed

Given: datasets X and Y

Test hypothesis using the Critical Value Method and the P-value Method

in

x

Two Samples Correlation: Two-Tailed

Given: datasets X and Y

Test hypothesis using the Critical Value Method and the P-value Method

in

x

Sample Data: Right-Tailed

Given: Contingency Table

Test for Independence using the Critical Value Method and the P-value Method

Please fill in the actual data values. Leave extra boxes blank, or put zeros.

in






The expected frequencies for each data value is listed below. Please ignore the zeros.