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Statistics for Data Analysis Using Excel
Statistical Data Analysis for beginners: Descriptive a Inferential statistics, Hypothesis testing.
This Course Includes
udemy
0 (28 reviews )
3h 29m 
english
Online - Self Paced
professional certificate
Udemy
About Statistics for Data Analysis Using Excel
Get marketable data analytic skills in this course using Microsoft Excel.
This course is about Statistics and Data Analysis. The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concept. Various examples and data-sets are used to explain the application. I will explain the basic theory first, and then I will show you how to use Microsoft Excel to perform these calculations.
Many tests covered, including different t tests, ANOVA, post hoc tests, correlation, and regression.
Following areas of statistics are covered:
Descriptive Statistics
- Mean, Mode, Median
Variability
- Standard Deviation, Variance, Range
Population and Sampling
Probability Distributions
Hypothesis Testing
- One Sample and Two Samples - z Test, t Test, p Test, F Test, Chi Square Test
ANOVA -
Perform Analysis of Variance (ANOVA) step by step doing manual calculation and by MS Excel.
Learning Objectives:
Explain how to calculate simple probability.
Review the Excel statistical formulas for finding mean, median, and mode.
Differentiate statistical nomenclature when calculating variance.
Identify components when graphing frequency polygons.
Explain how t-distributions operate.
Describe the process of determining a chi-square.
Enroll in this course and obtain important marketable data analytic skills
What You Will Learn?
- Learn all about Descriptive and Inferential Statistics with practical examples .
- Learn to use the power of Microsoft Excel to perform statistical calculations for you .
- Analyze a population using data samples .
- Get an idea about Central Limit Theorem .
- Calculate Co-variance and Co-relation among data .
- After finishing our Course you will be able to calculate the measures of central tendency, asymmetry, and variability .
- Perform hypothesis testing .
- Learn how to work with different types of data.