Descriptive Statistics for Data Analysis (PGMT8200)

Descriptive Statistics for Data Analysis

Descriptive Statistics for Data Analysis

Description:

Leaders and professionals require a basic understanding of statistics to properly analyze information and evaluate options. This introductory statistics course provides a foundation for analyzing data. The class begins with a review of arithmetic and algebra that is used in statistical calculations. Following the review, participants proceed to basic descriptive statistics, including percentages, averages, proportions and more. The emphasis throughout the course is on understanding; Understanding the concepts underlying the statistical formulas; Understanding which formula to use in a given analytic situation. Each concept is presented with examples then practiced with calculations and interpretations to increase understanding.

We strongly encourage you to also enroll in Inferential Statistics for Data Analysis (PGMT9200). These two courses work together to provide statistical knowledge for data analysis. The Inferential Statistics class begins immediately following this class. Both courses are required for the Level 1 and Level 2 Certificates of Accomplishment in Program and Management Analysis.

Who Should Attend?

  • Individuals needing to understand and/or perform basic statistical calculations and interpretations in their professional work
  • Decision makers and critical thinkers who analyze information and evaluate options to make decisions and recommendations
  • Individuals new to data analysis and statistics
  • Individuals seeking a refresher of basic descriptive statistical concepts

Tuition:

$949.00

Credits:

1.2 CEU's

Class Type:

This course is currently being offered in the following training modalities:

Learning Outcomes:

  • Describe and develop frequency distributions

  • Calculate proportions and percentages

  • Calculate measures of the average and the variation in quantitative data

  • Use proportions and percents to describe variation in categorical data

  • Describe normal distribution

  • Calculate and use z scores to identify probabilities under the normal distribution

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