Select Options and choose your Confidence level. Then select C1 for Sample 1 and C2 for Sample 2.) (If you have the raw data, enter the data for the first sample into C1 and for the second sample into C2 and select Each sample is in its own column. In the dropdown menu select Summarized data and input the sample size, sample mean, and sample standard deviation.
Select Stat, then Basic Statistics, and 2-Sample t. Two Sample t-Interval (Independent Samples)
For a confidence interval select a Mean ≠ hypothesized mean as the alternative hypothesis from the dropdown menu.Ĭlick OK on the Options window and OK on the main dialog window and the confidence interval is displayed in the Session window. Select Options and choose your confidence level. (Or if you have the raw data, enter the data into into C1 and select One or more samples, each in a column from the dropdown menu and then select C1.) In the dropdown menu select Summarized data and input the sample size, mean, and standard deviation. Select Stat, then Basic Statistics, and 1-Sample t. Enter the Confidence level and select Normal approximation from the second dropdown. Select Summarized data from the dropdown and enter Number of events and Number of trials.Ĭlick the Options button. Chi-Square Goodness-of-Fit Test for Observed Counts in Variable: Observed Observed and Expected Counts CategoryĬhoose Stat, select Basic Statistics and then choose 1 Proportion. Select Proportions specified by historical counts and choose your Expected column as the Input column. Select your Observed column for Observed counts. Note: The first row (labeled ‘Pearson’) under Chi-Square Test in the output corresponds to the methods used in the texts.Ĭhoose Stat, Tables, and Chi-Square Goodness-of-Fit Test (One Variable). Chi-Square Test for Association: Worksheet rows, Worksheet columns Rows: Worksheet rows Columns: Worksheet columns Under Columns containing the table, input column " C2 Yes" and column " C3 No". Select Summarized data in a two-way table from the dropdown. Select C1 as the input column.Ĭlick OK and the probability will appear in the Session window.Ĭhoose Stat, Tables, and Chi-Square Test for Association. Select Cumulative probability and enter the number for Degrees of freedom. Select C1 as the input column.Ĭlick OK and the critical value will appear in the Session window.Įnter the Chi-Square value in the first row of column C1. Go to Calc, Probability Distributions, Chi-Square.Ĭhoose Inverse cumulative probability and enter the number for Degrees of freedom. If the area we are given is to the right of the critical value, we must first determine the area to the left by calculating (1-area to the right). (Alternatively, Cumulative Probability)Ĭomplete the dialog box with Number of trials – " 12", Event probability – " 0.1", Input column – " x", and Optional storage – " p( x)".Įnter the area to the left of the desired critical value in the first row of column C1. Press Calc, Probability Distributions, and Binomial.ĭesignate Probability. Set up the worksheet in C1 and C2 as shown below. Select OK.īinomial Distribution Binomial Probability Distribution Use select to input C1 as Responses and C2, C3 as Factors. Under Stat, choose ANOVA, then General Linear Model, then Fit General Linear Model…. Enter the row numbers into C2 and the column numbers into C3. Press OK again.Įnter all the data into C1, one column at a time. Observe the results of Fisher's LSD test.Ĭlick on Comparisons and check the box for Tukey and for Tests. Press OK.Ĭlick on Comparisons and check the box for Fisher and for Tests. Select Options and enter the desired Confidence level.
Enter the corresponding data value in Column C2.Įnter the data for the Response and the categories for the Factor. One-way ANOVA: C1, C2, C3 Method Null hypothesisĮqual variances were assumed for the analysis.Įnter the category labels in Column C1. Highlight the appropriate columns in the box on the left. In the dropdown select Response data are in a separate column for each factor level.Ĭlick the mouse in the box labeled Responses. Enter the data for the different groups into separate columns.
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