## How to.

Create a geographic map to your liking using the leaflet map package in Displayr Follow instructions on How to Make a Geographic Map in Displayr…

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Generating high quality data from your online quantitative surveys is key to getting powerful insights and making data-driven decisions. Find out how.

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This post describes how to interpret the coefficients, also known as parameter estimates, from logistic regression (a.k.a. binary logit).

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Logistic regression (a.k.a. binary logit or binary logistic regression) is a predictive modeling technique used to predict outcomes involving two options

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When segmenting a market, a practical challenge is to work out the number of segments. There are eight approaches to choosing the number of segments.

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I'll show you three simple methods of analyzing free-form text data from open ended survey questions and explain when you might use each.

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In this post I explore the implications of using hierarchical Bayes versus using latent class analyis for data which contains segments.

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Most data scientists automatically use tidy data. In this post, I'll explain what tidy data is and why you'll want to consider an alternative, numerate data

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Traditionally, the primary statistic of interest for categorical data is the percentage of the cases in the data that fall into each category. However, there…

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How To Convert Text Dates To Numeric? Formatting and cleaning data is a crucial and often time-consuming step in any data analysis. One frequent step in this pr...

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Cluster analysis techniques require users to specify the number of clusters that they require. Six classes of approaches to choosing the number of clusters:

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Open-Ended Survey Questions occur when you run a survey and ask a respondent to enter some text as an answer, learn how to categorize these questions.

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Most of the widely used cluster analysis algorithms can be highly misleading or can simply fail when most or all the observations have some missing values.

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Latent class analysis requires the analyst to specify the number of classes prior to the application of the technique. Learn more about the seven approaches

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A practical challenge when working out how to segment is that there are usually lots of possible variables, and you need to reduce that number.

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Golden questions are used to allocate people to segments. They are also known as self-selection questions. The main applications of golden questions are:

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How to enter data from Paper Surveys. Displayr's Matt Engdahl explains the process in a step by step guide.

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This article discusses how to work out which segmentation variables are appropriate from a list of variables.

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