# StatCrunch Procedures – Summary (StatCrunch Help)

StatCrunch Procedures – Summary (StatCrunch Help)

Qualitative Data – Frequency or Relative Frequency Bar Graph

With Data:

Graph, Bar Plot, With Data, Select Column(s), Select Type (Frequency or Relative Frequency), Order By: Choose Worksheet, Display: Check the Value Above Bar, Optionally enter Graph Properties, Compute!

With Summary:

Graph, Bar Plot, With Summary, Categories in: Select column with names of categories,

Counts in: Select column with categories frequencies, Select Type (Frequency or Relative Frequency, Order By: Choose Worksheet, Display: Check the Value Above Bar, Optionally enter Graph Properties, Compute!

Qualitative Data – Frequency or Relative Frequency Distribution Table

With Data: Stat, Tables, Frequency, Select Column, Statistics: Choose desired statistic(s) (normally Frequency or Relative Frequency), Compute!

Relative Frequency With Summary: First Create a Relative Frequency Bar Graph as above; then

create the Distribution Table obtaining the Relative Frequencies from the Values above the Bars

Qualitative Data – Pareto Chart

Create a Bar Graph as above; In the Order By: Choose “Count Descending”

Qualitative Data – Pie Chart

Graph, Pie Chart, With Data or Summary, Display: Count and Percent of Total

5. Quantitative Data – Histogram (Frequency or Relative Frequency)

Graph, Histogram, Select Column(s) with Data, Select Type, Bins: Do not enter to use

StatCrunch defaults or enter desired values, Display options: Check the Value Above Bar, Optionally enter Graph Properties, Compute!

6. Quantitative Data – Distribution Table (Frequency or Relative Frequency)

First create a Histogram as above, then from the x-axis of the graph, determine width and starting point of each class, then determine corresponding Frequencies by reading the values above each bar

7. Summary Statistics

Stat, Summary Stats, Columns(s), Select the statistics you want. Select multiple by holding the CTRL key while clicking on a choice, Compute!

Note: for Standard Deviation:

Sample, choose Std. Dev.;

Population, choose Unadj. Std. Dev.

8. Quantitative Data – Mean for Grouped data

Stat, Summary Statistics, Grouped / Binned Data

Bins in: Classes

Counts in: Frequencies

Check Consecutive lower limits for Midpoint’s calculations

Choose the Statistic: mean, std. dev.

9. Quantitative Data – Weighted Mean

Stat, Calculators, Custom

Values in: Column containing the data whose average we are seeking Weights in: Column containing the weights

Compute!

10. Box Plot

Graph, Box Plot, Select Column(s), Check both of “Other Options”; On the generated Box Plot: Place the cursor over an outlier to get info about it. Place the cursor over the box plot to get info about the five-number summary.

11. Scatter Diagram (Plot)

Graph, Scatter Plot, Select X Variable column, Select Y Variable column, Display: Points, Optionally enter Graph Properties, Compute!

12. Correlation

Stat, Summary Stats, Correlation

13. Regression

Stat, Regression, Simple Linear, Select Column for X Variable, Select Column for Y Variable. (Optionally: enter Save: Residuals, Predicted values for Y: enter desired x value), Compute!

14. Discrete Probability Distribution: Mean & Std Dev

Stat, Calculators, Custom, Values in: Column containing the Discrete variable X,

Weights in: Column containing the Probabilities for X: P(X), Compute!

Binomial Probability

Stat, Calculators, Binomial

Normal Probability Distribution

Stat, Calculators, Normal

17. Find Areas (Probabilities) Under Normal Curve

Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean and Std. Dev., Select the inequality sign, Input the value for X, Compute!

NOTE: For the Standard Normal Curve, use Mean = 0 and Std. dev. = 1

18. Find X-value under a Normal Probability Curve

Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean and Std. Dev., Select the inequality sign, Input Probability (Area) in the Probability field (rightmost), Compute!

NOTE: For the Standard Normal Curve, use Mean = 0 and Std. dev. = 1

19. Normal Probability Plot (QQ Plot)

Graph, QQ Plot, Select Columns, ADD: Check Correlation Statistics, Other Options: Check Normal Quantiles on Y-axis, Compute!

20. T-Distribution

Stat, Calculators, T

21. Find Areas (Probabilities) Under t-Distribution Curve

Stat, Calculators, T, Select Standard or Between, Input the value for Degrees of

Freedom (n – 1), Select the inequality sign, Input the value for t, Compute!

22. Find t-value under a t-Distribution Curve

Stat, Calculators, T, Select Standard or Between, Input the value for Degrees of

Freedom (n – 1), Select the inequality sign, Input Probability (Area) in the Probability field (rightmost), Compute!

23. Find Areas (Probabilities) of x that is Normally Distributed

Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean

(µx = µ) and Std. Dev. (σx = σn), Select the inequality sign, Input the value for x, Compute!

24. Find Areas (Probabilities) of p that is Normally Distributed

Stat, Calculators, Normal, Select Standard or Between, Input the values for Mean

(µp = p) and Std. Dev. (σp= p(1-p)n), select the inequality sign, Input the

value for X ( p), Compute!

25. Confidence Interval – One Proportion

Stat, Proportion Stats, One Sample, With Summary (or With Data, if available), Input # of successes and observations, Select Confidence Interval Level (leave Method as is), Compute!

26. Confidence Interval – Proportion – Sample Size

Stat, Proportion Stats, One Sample, Width/Sample Size, Confidence Level: enter desired level, Target proportion if given, otherwise enter 0.5, Width (twice the Error)

27. Find Critical Value zα2

Stat, Calculators, Normal, Select Standard, Input Mean = 0 and Std. Dev =1,

Select the inequality sign for ≥, enter the α2 value in the Probability field (rightmost), Compute!

28. Confidence Interval – One Mean

Stat, T Stats, One Sample, With Summary (or With Data, if available), Input Sample Mean, Sample Std. Dev, Sample Size, Select Confidence Interval and Input the Desired Confidence Level, Compute!

29. Confidence Interval – Mean – Sample Size

Stat, T Stats, One Sample, Width/Sample Size, Confidence level: desired level, Std. Dev., Width: twice error, Compute!

30. Find Critical Value tα2Stat, Calculators, T, Select Standard, Degrees of Freedom (n-1),

Select the inequality sign for ≥, enter the α2 value in the Probability field (rightmost)

31. Confidence Interval – Variance or Standard Deviation

Stat, Variance Stats, One Sample, With Summary (or With Data, if available), Input Sample Variance, Sample size, Select Confidence Interval and Input the Desired Confidence Level, Compute!

32. Find Critical Value χ1-α22 and χα22Stat, Calculators, Chi-Square, Select Between, Degrees of Freedom (n-1), enter the (1−α) value in the Probability field (rightmost), Compute!

Hypothesis Testing – One Population Proportion

Stat, Proportion Stats, One Sample, With Summary (or With Data, if available)

Hypothesis Testing – One Population Mean

Stat, T Stats, One Sample, With Summary (or With Data, if available)

Hypothesis Testing – One Population Variance, Standard Deviation

Stat, Variance Stats, One Sample, With Summary (or With Data, if available)

Hypothesis Testing – Two Populations Proportions

Stat, Proportion Stats, Two Samples, With Summary (or With Data, if available)

Hypothesis Testing – Two Means: Dependent (Paired) Samples

Stat, T Stats, Paired, Good idea to Save differences by clicking on the check box

Hypothesis Testing – Two Means: Independent Samples

Stat, T Stats, Two Samples, With Summary (or With Data, if available)

Hypothesis Testing – Goodness of Fit

Stat, Goodness-of-Fit, Chi-Square test

40. Hypothesis Testing – Test of Independence

Stat, Tables, Contingency, With Summary:

In the Select Columns area, choose the Columns containing the values of the Column Variable

In the Row Labels, choose the column containing the name of the Row Variable

In the Display area choose “Expected Counts”

In the Hypothesis tests area, choose “Chi-Square test for independence”

41. Hypothesis Testing – Test the Homogeneity of Proportions

Same procedure as for Test of Independence

42. Comparing Three or more Means (ANOVA)

Stat, ANOVA, One Way, Choose the columns containing the three or more samples.

43. Two-Way Analysis of Variance (ANOVA)

In column var1, enter the level of factor A; in column var2, enter the level of factor B; and in column var3, enter the value of the response variable. Name the columns.

Stat, ANOVA, Two Way, Select the column containing the values of the response variable from the pull-down menu “Responses in:”,

Select the column containing the row factor in the pull-down menu “Row factor in:”,

Select the column containing the column factor in the pull-down menu “Column factor in:”, Select the “Plot interactions” box for Interaction Plots and “the Compute Tukey HSD” box to conduct Tukey’s test, To save residuals to draw a normal probability plot, highlight Residuals under Save:, Compute!

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