# Enter your data for Analysis of Means

Stat > ANOVA > Analysis of Means

Select the option that best describes your data.

## Enter normally distributed data

Complete the following steps if your data follow a normal distribution.

1. In Response, enter the numeric column of data that you want to analyze. Normally distributed data are typically measurement data, such as weight. With normally distributed data, Minitab compares the mean of each group to the overall mean.
2. Under Distribution of Data, select Normal.
3. In Factor 1, enter the column that contains the levels for the first factor. If you enter a single factor, Minitab produces a single plot showing the means for each level of the factor.
4. (Optional) In Factor 2, enter a column that contains the levels for the second factor. If you enter two factors, Minitab produces an interaction plot and a main effects plot for each factor.
In this worksheet, Density is the response and contains density measurements. Minutes and Strength are factors 1 and 2 and may explain differences in the density measurements.
C1 C2 C3
Density Minutes Strength
0 10 1
5 15 1
2 18 2
4 10 2

## Enter binomial data

Complete the following steps if your data follow a binomial distribution.

1. In Response, enter the column that contains the counts of events in each sample, such as the number of defectives. With binomial data, Minitab compares the proportion of each sample to the overall proportion.
2. Under Distribution of Data, select Binomial.
3. In Sample size, enter the number of observations contained in each sample. Each sample must have the same number of observations. The sample size must be large enough to ensure that the normal distribution adequately approximates the binomial distribution because the decision limits are based on the normal distribution. The normal distribution is adequate when np > 5 and n(1 − p) > 5, where n is the sample size and p is the proportion of events.
In this worksheet, Pipes is the response. Each row represents the number of defective pipes counted in samples of 100 pipes. For example, inspectors record 1 defective pipe in the first sample and 6 defective pipes in the second sample
C1
Pipes
1
6
3
9

## Enter Poisson data

Complete the following steps if your data follow a Poisson distribution.

1. In Response, enter the column of Poisson data that you want to analyze. Poisson data contain counts, such as the number of defects per unit or sample. With Poisson data, Minitab compares the rate of occurrence for each sample to the overall rate. Each sample should have the same number of observations. The sample size must be large enough to ensure that the normal distribution adequately approximates the Poisson distribution because the decision limits are based on the normal distribution. The normal distribution is adequate when the mean is at least 5.
2. Under Distribution of Data, select Poisson.
In this worksheet, Defects is the response. Each row represents the number of defects counted in samples of 50 cell phones. For example, the inspectors count 2 defects in the first sample of 50 cell phones and 4 defects in the second sample of 50 cell phones
C1
Defects
2
4
1
5
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