This article provides guidance for Extension professionals on correctly analyzing Likert data. Likert-type and Likert scale data require specific analysis methods, and errors often occur due to misunderstanding these differences. The article explains the distinction between Likert-type items (single questions with Likert response options) and Likert scales (multiple questions combined into a composite score). It also discusses the appropriate statistical procedures for each type of data. Likert-type items are ordinal data, and their analysis should include measures such as mode, median, and frequencies. Likert scales, on the other hand, are treated as interval data and should be analyzed using mean and standard deviation. Additional analysis methods for Likert scales include Pearson's r, t-test, ANOVA, and regression. The decision on how to analyze Likert data should be made during questionnaire development. If the questions are individual and not combined, they should be treated as Likert-type items. If the questions are combined to measure a trait or attitude, they form a Likert scale and should be analyzed as interval data. If individual items need to be reported, only Likert-type statistical procedures should be used. Once the decision between Likert-type and Likert scale is made, the appropriate statistical methods will be clear.This article provides guidance for Extension professionals on correctly analyzing Likert data. Likert-type and Likert scale data require specific analysis methods, and errors often occur due to misunderstanding these differences. The article explains the distinction between Likert-type items (single questions with Likert response options) and Likert scales (multiple questions combined into a composite score). It also discusses the appropriate statistical procedures for each type of data. Likert-type items are ordinal data, and their analysis should include measures such as mode, median, and frequencies. Likert scales, on the other hand, are treated as interval data and should be analyzed using mean and standard deviation. Additional analysis methods for Likert scales include Pearson's r, t-test, ANOVA, and regression. The decision on how to analyze Likert data should be made during questionnaire development. If the questions are individual and not combined, they should be treated as Likert-type items. If the questions are combined to measure a trait or attitude, they form a Likert scale and should be analyzed as interval data. If individual items need to be reported, only Likert-type statistical procedures should be used. Once the decision between Likert-type and Likert scale is made, the appropriate statistical methods will be clear.