Statistics and Data Analysis ( الإحصاء وتحليل البيانات)

Learn how to apply probability and statistics to solve real problems and take decisions in business

4.95 (21 reviews)
Udemy
platform
العربية
language
Engineering
category
Statistics and Data Analysis ( الإحصاء وتحليل البيانات)
176
students
20.5 hours
content
Jan 2024
last update
$39.99
regular price

What you will learn

Understand the basics of probability theory

Perform descriptive statistics calculations

Present results in different graphical formats

Perform basic probability theorems and Bayes' theorem

Understand and Perform probability calculations for discrete probability density functions

Using Binomial, Hypergeometric, and Poisson distributions

Understand and Perform probability calculations for continuous probability density functions

Using Normal distribution

Perform calculations for the sampling distribution of the mean (central limit theorem) and the variance (χ2 and F distributions).

Understand and perform calculations for parameter estimation

Perform hypothesis testing

Perform simple linear regression and correlation

Combination and Permutation

Calculate Covariance

Linear Combination of variables

Why take this course?

Welcome to Engineering Statistics and Probability Theory

This course will go over theories and implementation of engineering statistics and probability theories to real business problems. Each section has many examples, quizzes, and assessment exams.

Our course includes professional HD Videos with extensive case studies to show you how to apply this knowledge to solve real and practical problems.

In this course we will cover:

  • Introduction to statistics and probability

  • Why Study Statistics?

  • Types of data

  • Definitions: Populations, units, and Sample

  • Generation of random number table

  • The difference between Parameters & Statistics

  • Branches of Statistics (Descriptive and Inferential statistics)

  • Pareto chart

  • Dot plot

  • Scatter plot

  • Frequency distribution

  • Histogram

  • Stem and Leaf display

  • Measures of Central Tendency (Mean, Median, and Mode)

  • Measures of Variation (Range, Variance and Standard Deviation)

  • Weighted Mean

  • Standard Deviation for Grouped Data

  • Coefficient of variation

  • Definitions (Probability experiment, Outcome, Sample space, and Event)

  • Types of Probability

  1. Classical (or theoretical) Probability

  2. Empirical (or statistical) Probability

  3. Subjective Probability

  • Combining events

  • Counting Principles

  • Multiplication of choices

  • Permutation

  • Combination

  • The Axioms of Probability

  • Venn diagrams

  • The Addition Rule

  • Mutually Exclusive Events

  • Conditional Probability

  • The Multiplication Rule

  • Independent Events

  • Bayes’ Theorem

  • Discrete Probability Distributions

  • Types of Random Variables

  • Discrete Probability Distributions (DPD)

  • Binomial Distribution

  • Hypergeometric Distribution

  • Poisson Distribution

  • Mean, Variance, and Standard Deviation of DPD

  • Continuous Probability Distributions

  • Normal Distribution

  • The Standard Normal Distribution

  • The Standard Normal Distribution Tables

  • The Normal Approximation to the Binomial Distribution

  • Sampling distributions

  • Populations and Samples

  • The Sampling Distribution of the Mean

  • The Sampling Distribution of the Mean (σ Known) –> z-distribution

  • The Sampling Distribution of the Mean (σ Unknown) –> t-distribution

  • Sampling Distribution of the Variance –> χ2-distribution

  • F - Distribution

  • Estimation of Population’s

  • Estimation of Population’s Mean

  • Point Estimation

  • Interval Estimation

  • Normal (s known). Or n ³ 30

  • Normal (s Unknown).

  • Calculation of Sample Size

  • Tests of Hypotheses

  • Introduction to Hypothesis Testing

  • Type I and type II errors

  • Level of Significance

  • Hypotheses Testing Process

  • Test Statistic Selection

  • Statistical Decision

  • Hypothesis Testing for the Population’s Mean:

  • Large Samples; n ≥ 30 or Normal population (σ Known) à (z)

  • Small Samples: n < 30 and Normal population (σ Unknown) à (t)

  • Tests of Hypotheses Using P-value

  • Hypothesis Testing for Proportions

  • Correlation and Regression

  • Correlation Coefficient r

  • scatter plot

  • Correlation Coefficient

  • Linear Regression

  • Regression Line

  • Linear combination of variables

  • Covariance

  • Correlation using covariance

  • and much more!

Screenshots

Statistics and Data Analysis ( الإحصاء وتحليل البيانات) - Screenshot_01Statistics and Data Analysis ( الإحصاء وتحليل البيانات) - Screenshot_02Statistics and Data Analysis ( الإحصاء وتحليل البيانات) - Screenshot_03Statistics and Data Analysis ( الإحصاء وتحليل البيانات) - Screenshot_04

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4621162
udemy ID
3/31/2022
course created date
5/8/2022
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