In this episode, co-hosts Jennifer Miller and Ron Landis continue their conversation about developing a measure of employee engagement. This episode is the second part of a discussion about how to use a statistical technique called factor analysis to examine the dimensions of employee engagement.In this episode, we had conversations around these questions: What is rotation in factor analysis?How do we determine the number of factors to retain?How do we identify which items load on which...
Jul 22, 2022
27 min
In this episode, co-hosts Jennifer Miller and Ron Landis continue their conversation about developing a measure of employee engagement. In this episode they focus on how to use a statistical technique called factor analysis to examine the dimensions of employee engagement. In this episode, we had conversations around these questions: What is factor analysis? What is the difference between exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)? What is t...
Jul 8, 2022
28 min
In this episode, co-hosts Jennifer Miller and Ron Landis continue their conversation about developing a measure of employee engagement. They identify and discuss several steps/phases that should be present when we develop measures of any kind. In this episode, we had conversations around these topics: Aspects of item writing were discussed. In particular, we talked about making sure that we carefully consider how items will be read and interpreted by people who will respond to the...
Jul 1, 2022
27 min
In this episode, co-hosts Jennifer Miller and Ron Landis start their conversation about developing a measure of employee engagement. They identify and discuss several steps/phases that should be present when we develop measures of any kind. In this episode, we had conversations around: The importance of clearly, accurately, and comprehensively defining what it is that we are interested in measuring (e.g., engagement). As part of the definition process, the importance of thinki...
Jul 1, 2022
26 min
In this episode, co-hosts Jennifer Miller and Ron Landis continue their discussion on the importance of data cleaning and management. They review three of five aspects of data cleaning that are critical to checking prior to the analytic phase. In this episode, they discuss how to check for linearity and normality, outliers, and multicollinearity. In this episode, we had conversations around these questions: How do you check for linearity and normality in a data set? Wh...
Jun 10, 2022
32 min
In this episode, co-hosts Jennifer Miller and Ron Landis discuss the importance of data cleaning and management. They identify five aspects of data cleaning that are critical to checking prior to the analytic phase. In some cases, data management is often embedded in the data encoding and storage process (I.e., certain rules are in place to ensure that data fields can only handle one type of data such as a date). In this episode, they discuss how to check for data accuracy and what to do with...
Jun 3, 2022
33 min
In another technically focused episode, co-hosts Jennifer Miller and Ron Landis discuss how to use multiple linear regression to test models involving moderation (or interaction). In episode 18, we discussed multiple linear regression in which we used multiple variables to predict the outcome or criterion variable. But what happens if you have a situation in which the relation between the predictor and outcome variable is actually dependent upon (or is conditional upon) the level of a third v...
May 27, 2022
32 min
In this episode, co-hosts Jennifer Miller and Ron Landis discuss the emerging field of artificial intelligence (AI). In particular, they discuss machine learning and two broad categories of algorithms, unsupervised and supervised learning. In this podcast episode, we had conversations around these machine learning questions: What is artificial intelligence? What is machine learning? What are some applications of machine learning in People Analytics? What is the d...
May 20, 2022
30 min
Earlier in this season, we discussed a commonly used technique called simple linear regression. In this technique, we used one variable to predict an outcome. But, let's face it – life is a little bit more complex than just having one predictor and many times, organizations have lots of data that can be used to predict an outcome. In another technically focused episode, co-hosts Ron Landis and Jennifer Miller deconstruct multiple linear regression. They focus on using multiple predictors to p...
May 13, 2022
31 min
In this episode, Ron Landis and Jennifer Miller deconstruct the importance of utilizing descriptive statistics as the foundation of starting the data analytic process. As many advanced statistical techniques are built on descriptives such as the mean and standard deviation, it is imperative to understand the characteristics of the data set being analyzed. In this episode, they have conservations around the following questions: What are the various ways in which central tendenc...
May 6, 2022
31 min
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