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Descriptive Statistics and Visualizing Data

  • A Beginner’s Guide To Using Descriptive Statistics, Creating Charts and Pivot Tables, and Visualization for Business
  • Free tutorial
  • Rating: 4.4 out of 54.4 (107 ratings)
  • 3,009 students
  • 1hr 12min of on-demand video
  • Created by Justin Bateh, Ph.D.
  • English

What you’ll learn

  • Calculate descriptive statistics using Excel
  • Create graphical representations of data using Excel
  • Create Pivot Tables
  • Create Bar Charts
  • Create Forecasted Trend Lines
  • Describe measures of center
  • Describe variability with the range and interquartile range (IQR)
  • Describe variability with the variance and standard deviation

Requirements

  • This course is intended for beginners. No prior statistics knowledge is required.

Description

Visualizing Data

The data visualization process aims to make sense of the raw data, presenting it in a manner that is easy to understand even for non-experts.

Not everyone you are presenting data to will understand statistics, but most people can look at a visual and tell what the story is!

For example:

  • Pie charts and bar charts are the most commonly used data visualization techniques; they can be created easily using standard spreadsheet programs like Microsoft Excel.
  • Numerical data can be represented in histograms, while categorical data can be visualized using frequency tables and charts.
  • Cumulative frequencies count the number of data points up to a given value and are used to find the median, quartile, and percentiles in a data group.
  • Relative frequency represents how often something happens relative to some total. For example, the relative frequency may be used to show that a given sales team won 10 of its last 13 contracts, while the cumulative frequency will show the median number of contracts won across the entire year.
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Visualizing data is an important skill, and that ability is essential whether running a business or teaching a class.

You can get a sense of the importance of the data by looking at numbers on a spreadsheet, but a well-chosen visual representation of that data can be much more helpful.

Descriptive Statistics and Numerical Data Summary

Charts and graphs are useful for representing data in a user-friendly format, but there are times when it is more important to summarize data numerically.

A quality numerical data summary has meaning even to individuals who have no previous experience with the data being presented. You do not have to be a scientist or a doctor to understand that the average cholesterol for a given male population is 220, while the cholesterol level for women in the same population is 190.

For example:

To understand the power of numerical data summary, it is important to understand the difference between the median and the mean:

  • the mean is the average of all observations, while the median is the point at which half the numbers are larger, and half are smaller.
  • The mode is another important numerical data representation: it is the observation that occurs most frequently.
  • The mean, median, and mode are important, but so is the variance.
  • The term variance is used to measure how widely, or narrowly, spread out a group of numbers is. For instance, a set of numbers in which all values are 7 has zero variance. These terms summarize a set of numbers and help the observer make sense of the results.

Whether the data being represented is a list of baseball statistics, salary data for a Fortune 500 company, or the cholesterol levels of heart patients, the summarization techniques are the same.

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Who this course is for:

  • Anyone interested in data analysis for improving quality and processes in business and industry
  • Anyone who wants to be a Data Analyst, Business User, Functional Consultant, Administrator, Solutions Architect, Developer
  • Any manager or businessperson responsible for decision-making
  • Anyone who wants to learn statistics for business analytics
  • Anyone interested in a career in data science or business analytics
  • Business executives
  • Individuals who are passionate about numbers

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Course content

5 sections • 11 lectures • 1h 14m total lengthCollapse all sections

Welcome from Dr. Justin Bateh!1 lecture • 2min

  • Welcome!01:31

Introduction To Basic Data Analysis and Statistics for Business3 lectures • 23min

  • Introduction02:25
  • Theoretical Tutorial18:37
  • Company Scenarios01:28

Describing Data: Using Descriptive Statistics To Tell The Story Of Your Data3 lectures • 15min

  • Introduction01:56
  • Theoretical Tutorial08:19
  • Guided Demonstration04:51

Visualizing Data with Graphs, Charts, Pivot Tables, and More3 lectures • 35min

  • Introduction02:19
  • Theoretical Tutorial05:03
  • Guided Demonstration27:27

BONUSES: TWO FINAL TASKS and BIG DISCOUNTS!1 lecture • 1min

  • BONUS and BIG DISCOUNT ON FULL COURSE!00:31

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