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Python Guide for the Total Beginner
MP4 | Video: AVC 1280 x 720 | Audio: AAC 48 KHz 1ch | Duration: 04:10:01 | 5.07 GB
Genre: eLearning | Language: English



"Python Guide for the Total Beginner"

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Python Guide for the Total Beginner
MP4 | Video: AVC 1280 x 720 | Audio: AAC 48 KHz 1ch | Duration: 04:10:01 | 5.07 GB
Genre: eLearning | Language: English




Understanding statistics is more important than ever. Statistical operations are the basis for decision making in fields from business to academia. However, many statistics courses are taught in cookbook fashion, with an emphasis on a bewildering array of tests, techniques, and software applications. In this course, part one of a series, Joseph Schmuller teaches the fundamental concepts of descriptive and inferential statistics and shows you how to apply them using Microsoft Excel.

He explains how to organize and present data and how to draw conclusions from data using Excel's functions, calculations, and charts, as well as the free and powerful Excel Analysis ToolPak. The objective is for the learner to fully understand and apply statistical concepts-not to just blindly use a specific statistical test for a particular type of data set. Joseph uses Excel as a teaching tool to illustrate the concepts and increase understanding, but all you need is a basic understanding of algebra to follow along.

Topics include:

Identify functions and charts available for use in Excel.
Recognize the definition of the Bayesian probability.
List the three measures of central tendency.
Compare the usage of inferential statistics to the usage of standard normal distribution.
Calculate the confidence level when provided the alpha level of uncertainty.
Define a Type I and Type II error of hypothesis testing.
Explain when to use a z-test or a t-test.
Recall the types of variance that occur in multi-factored studies.
Summarize the function of variables in multiple regression.
Name three types of correlation values.
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Python Guide for the Total Beginner


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