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Complete Statistics For Business Analysis & Data Science

Name: Complete Statistics For Business Analysis & Data Science
Rating: 4.4 (27 reviews)

Probability, Distribution, Descriptive Analysis, Correlation & Regression analysis ,Research Analysis

Created byIftikhar Ali

Last updated 10/2023

English

What you'll learn

Understand Fundamentals Of Statistics
Implement Basic Statistics
Understand Various Statistical Distributions
Understanding Regression & Measures of Dispersion
Time Series AnalysisBe able to understand different types of data
Understanding Correlation And Regression Analysis
Understanding Skewness & Kurtosis
How to plot different types of Data
Understanding In depth Index Numbers
Probability

Course content

13 sections • 187 lectures • 18h 49m total length

Introduction3:58
Introduction
Chapter 1:1 Introduction to Statistics4:31
Introduction to Course Contents
Chapter 1:2 Introduction to Statistics5:54
Introduction to Statistics
Chapter 1:3 Introduction to Statistics2:32
Branches of Statistics
Chapter 1:4 Introduction to Statistics5:00
Population vs. Sample
Is Sample a true representative of population or not?
Chapter 1:5 Introduction to Statistics2:35
Parameter vs. Statistic
Chapter 1:6 Introduction to Statistics5:37
Data and its Types
Editing of Data
Types of Data
Primary data
Secondary data
Chapter 1:7 Introduction to Statistics4:44
Quantitative data
Qualitative data
Discrete data
Continuous data
Chapter 1:8 Introduction to Statistics2:37
Variable vs. Constant
Types of Variables
Chapter 1:9 Introduction to Statistics2:36
Dependent or Responding Variable
Independent and Explanatory Variable
Chapter 1:10 Introduction to Statistics1:31
Discrete Variable
Continuous Variable
Chapter 1:11 Introduction to Statistics4:37
Quantitative Variable
Qualitative Variable
Categorical or Nominal Variable
Confounding Variable
Endogenous Variable
Exogenous Variable
Chapter 1:12 Introduction to Statistics8:38
Binary or Dichotomous Variable
Random Variable
Intervening Variable
Census

Chapter 2:1 Presentation of the Data9:53
Introduction
Classification
Types of Classification
Attributive or Qualitative Classification (Simple Classification)
Attributive or Qualitative Classification (Two way Classification)
Chapter 2:2 Presentation of the Data6:17
Quantitative Data:
(i) Arrayed data or series of individual observations
(ii) Discrete Data or Discrete Frequency Distribution
Chapter 2:3 Presentation of the Data8:18
(i) Frequency Distribution of Grouped Data
Chapter 2:4 Presentation of the Data6:38
Class Boundaries
Inclusive Class & Exclusive Class
Class Mark
Cumulative Frequency
Height of the Class/ Class Interval
Chapter 2:5 Presentation of the Data5:34
Graphical Presentation of the Data
Bar Diagrams
Simple Bar Diagram or Chart
Multiple Bar Diagram/Chart
Sub-divided Bars or Component Bar Chart
Chapter 2:6 Presentation of the Data2:42
Rectangles
Chapter 2:7 Presentation of the Data2:17
Pie Diagram
Chapter 2:8 Presentation of the Data1:59
Historigram
Chapter 2:9 Presentation of the Data7:14
Statistical Data & Graphs or Graphs of Frequency Distribution
Histogram
Frequency Polygon
Cumulative Frequency Polygon

Chapter 3: 1 Measures of Central Tendency5:22
Introduction to Measures of Central Tendency
Chapter 3: 2 Measures of Central Tendency6:59
Characteristics or Essentials of a Good Average
Types of Averages
Arithmetic Mean
Properties of Arithmetic Mean
Chapter 3: 3 Measures of Central Tendency4:44
Formulas for Arithmetic Mean for Ungrouped & Grouped Data
Chapter 3: 4 Measures of Central Tendency4:59
Calculation of Arithmetic Mean for Ungrouped Data
Chapter 3:5 Measures of Central Tendency6:27
Calculation of Arithmetic Mean for Grouped Data
Chapter 3: 6 Measures of Central Tendency3:17
Weighted Mean & its Calculation
Chapter 3:7 Measures of Central Tendency2:47
Trimmed Mean & its Calculation
Chapter 3: 8 Measures of Central Tendency1:44
Winsorized Mean & its Calculation
Chapter 3: 8 Measures of Central Tendency5:34
Median
Calculation of Median for Ungrouped Data
Chapter 3: 9Measures of Central Tendency5:19
Calculation for Median for Grouped Data
Chapter 3: 10 Measures of Central Tendency3:55
Calculation for Median for Grouped Data
Chapter 3:11 Measures of Central Tendency5:03
Mode
Calculation of Mode for Ungrouped Data
Chapter 3: 12 Measures of Central Tendency3:11
Calculation for Mode for Grouped Data
Chapter 3: 13 Measures of Central Tendency2:21
Calculation for Mode for Grouped Data
Chapter 3: 14 Measures of Central Tendency3:22
Empirical Method for Mode & its Calculation
Chapter 3: 15 Measures of Central Tendency5:07
Harmonic Mean, its Formulas & Calculation for ungrouped data
Chapter 3: 16 Measures of Central Tendency3:14
Harmonic Mean & its Calculation for Grouped Data
Chapter 3: 17 Measures of Central Tendency5:09
Geometric Mean, its Formulas & Calculation for ungrouped data
Chapter 3: 18 Measures of Central Tendency4:27
Calculation of Geometric Mean, Mean & Harmonic Mean for Grouped Data
Chapter 3: 19 Measures of Central Tendency7:52
Quartiles, Deciles, Percentiles
Formulas for Quartiles for Ungrouped & Grouped Data
Chapter 3: 20 Measures of Central Tendency4:55
Formulas for Deciles & Percentiles for Ungrouped & Grouped Data
Chapter 3: 21 Measures of Central Tendency6:33
Calculation of Quartiles, Deciles & Percentiles for Ungrouped Data
Chapter 3: 22 Measures of Central Tendency12:08
Calculation of Quartiles, Deciles & Percentiles for Grouped Data

Chapter 4:1 Measures of Dispersion3:20
Introduction to Measures of Dispersion
Chapter 4:2 Measures of Dispersion6:50
Absolute Measures of Dispersion
Relative Measures of Dispersion
Chapter 4 :3 Measures of Dispersion3:07
Various Absolute & Relative Measures of Dispersion
Chapter 4:4 Measures of Dispersion3:17
Range
Absolute Range
Coefficient of Range
Chapter 4:5 Measures of Dispersion2:01
Calculation of Range and Coefficient of Range for ungrouped data
Chapter 4:6 Measures of Dispersion2:25
Calculation of Range and Coefficient of Range for Grouped data
Chapter 4:7 Measures of Dispersion1:43
Calculation of Range and Coefficient of Range for Grouped data
Chapter 4:8 Measures of Dispersion2:09
Quartile Deviation or Semi Inter Quartile Range
Formulas for Absolute & Relative measures Quartile Deviation or Semi Inter Quartile Range
Chapter 4:9 Measures of Dispersion3:06
Calculation of Quartile Deviation or Semi Inter Quartile Range & Coefficient of Quartile Deviation for ungrouped data
Chapter 4:10 Measures of Dispersion6:17
Calculation of Quartile Deviation or Semi Inter Quartile Range & Coefficient of Quartile Deviation for Grouped data
Chapter 4:11 Measures of Dispersion3:50
Mean Deviation
Mean Deviation from Mean & Coefficient Formulas
Mean Deviation from Median & Coefficient Formulas
Mean Deviation from Mode & Coefficient Formulas
Chapter 4:12 Measures of Dispersion6:38
Mean Deviation through Mean, Median & Mode & their respective coefficients Ungrouped Data
Chapter 4:13 Measures of Dispersion10:14
Mean Deviation through Mean, Median & Mode & their respective coefficients Grouped Data
Chapter 4:14 Measures of Dispersion7:13
Standard Deviation & Variance
Properties of Standard Deviation
Chapter 4:15 Measures of Dispersion5:20
Formulas for Standard Deviation & Coefficient of Standard Deviation (Both Ungrouped Data & Grouped Data)
Formulas for Variance & Coefficient of Variation (Both Ungrouped Data & Grouped Data)
Chapter 4:16 Measures of Dispersion4:48
Calculation of Standard Deviation, Variance & their Coefficients for ungrouped Data
Chapter 4:17 Measures of Dispersion6:51
Calculation of Standard Deviation, Variance & their Coefficients for Grouped Data
Chapter 4:18 Measures of Dispersion4:58
Symmetry & Skewness
Positive Skewness
Negative Skewness
Chapter 4:19 Measures of Dispersion8:47
Karl Pearson Coefficient of skewness Formula 1
Karl Pearson Coefficient of skewness Formula 2
Bowley’s Coefficient of skewness
Calculation of absolute skewness & Coefficient of Skewness in ungrouped data
Chapter 4:20 Measures of Dispersion11:09
Calculation of absolute skewness & Coefficient of Skewness in Grouped data
Chapter 4:21 Measures of Dispersion5:18
Moments & Kurtosis
Moments about Mean (Formulas)
Chapter 4:22 Measures of Dispersion1:11
Moments about Orihin or Zero (Formulas)
Chapter 4:23 Measures of Dispersion3:33
Moments about Provisional Mean or Arbitrary Value (Non Central Moment) Shortcut Method
Moments about Provisional Mean or Arbitrary Value (Non Central Moment) Coding or Step Deviation Method
Chapter 4 :24 Measures of Dispersion9:03
Calculation of moments and Kurtosis related to Grouped Data

Chapter 5:1 Index Numbers1:56
§ Initial Introduction
Chapter 5:2 Index Numbers4:04
§ Introduction of Index Numbers
Chapter 5:3 Index Numbers1:52
§ Simple & Composite Index
Chapter 5:4 Index Numbers1:09
§ Types of Index Numbers
§ Price Index
§ Quantity Index
§ Weighted & Aggregative Index
Chapter 5:5 Index Numbers4:58
§ Steps in construction of index numbers
§ Difference between weighted & un-weighted index numbers
Chapter 5:6 Index Numbers2:16
§ Important uses of index numbers
Chapter 5:7 Index Numbers1:52
§ Diagrammatical Representation of Methods & Types
Chapter 5:8 Index Numbers1:39
§ Diagrammatical Representation of Weighted & Un-weighted Index
Chapter 5:9 Index Numbers3:20
§ Difference between fixed base and chain base
Chapter 5:10 Index Numbers6:17
§ Formulas & Calculations
Chapter 5:11 Index Numbers4:48
§ Calculation of Simple Index Number (Fixed Base method)
Chapter 5:12 Index Numbers2:15
§ Calculation of Simple Index Number (Fixed Base method)
Chapter 5:13 Index Numbers3:16
§ Calculation of Simple Index Number (Fixed Base method)
Chapter 5:14 Index Numbers2:51
§ Calculation of Simple Index Number (Fixed Base method)
Chapter 5:15 Index Numbers5:16
§ Calculation of Simple Index Number (Chain Base method)
Chapter 5:16 Index Numbers7:27

§ Composite Index Un-weighted Methods
§ Calculation of composite index number (Aggregative method)
Chapter 5:17 Index Numbers8:55
§ Calculation of composite index number (average of relative method using price relative)
Chapter 5:18 Index Numbers6:40
§ Calculation of composite index number (average of relative method using Chain index)
Chapter 5:19 Index Numbers8:04
§ Calculation of composite index number (average of relative method using Chain index)
Chapter 5:20 Index Numbers6:42
§ Calculation of composite index number (average of relative method using Chain index)
Chapter 5:21 Index Numbers3:56
§ Composite Index Weighted Methods
Chapter 5:22 Index Numbers11:29
§ Calculation of weighted index through all five methods
(1) Laspeyre’s index or Base year weighted
(2) Paasche’s index or current year weighted
(3) Fisher’s Ideal index
(4) Marshal Edgeworth’s index
(5) Walsh index
Chapter 5:23 Index Numbers4:42
§ Consumer price index (CPI)
§ Methods of Calculation Consumer Price Index
§ Aggregative Expenditure Method
§ Family Budget Method
Chapter 5:24 Index Numbers10:52
§ Calculation of Consumer’s Price Index number through Aggregative Expenditure Method & Family Budget Method

Chapter 6:1 Correlation & Regression7:10

§ Introduction of the Chapter
Chapter 6:2 Correlation & Regression6:56
§ Types of Correlation
§ Positive
§ Negative
§ Perfectly Positive
§ Perfectly Negative
§ Zero or No Correlation
Chapter 6:3 Correlation & Regression4:56
§ Properties of Correlation
§ Uses of Correlation
Chapter 6:4 Correlation & Regression6:26
§ Coefficient Calculation of Correlation (Formula 1)
Chapter 6:5 Correlation & Regression6:32
§ Calculation of Correlation Coefficient (Formula 2)
Chapter 6:6 Correlation & Regression4:23
§ Calculation of Correlation Coefficient (Formula 3)
Chapter 6:7 Correlation & Regression3:42
§ Calculation of Correlation Coefficient (Formula 4)
Chapter 6:8 Correlation & Regression2:07
§ Calculation of Correlation Coefficient (Other Formulas)
Chapter 6:9 Correlation & Regression6:00
§ Rank Correlation
§ Assumptions of Rank Correlation
§ Methods to Calculate Rank Correlation Coefficient
§ Spearman’s Rank Correlation Coefficient
§ Kendall Tau-b Rank Correlation Coefficient
§ Goodman & Kruskal’s Gamma Coefficient of Rank Correlation
Chapter 6:10 Correlation & Regression5:16
§ Spearman’s Rank Correlation Coefficient (Calculation with data has no ties)
Chapter 6:11 Correlation & Regression6:16
§ Spearman’s Rank Correlation Coefficient (Calculation with data has ties)
Chapter 6:12 Correlation & Regression12:44
§ Kendall Tau-b Rank Correlation Coefficient (Calculation)
Chapter 6:13 Correlation & Regression6:42
§ Kendall Tau-b Rank Correlation Coefficient (Calculation)
Chapter 6:14 Correlation & Regression9:18
§ Goodman & Kruskal’s Gamma Coefficient of Rank Correlation (Calculation)
Chapter 6:15 Correlation & Regression3:48
§ Goodman & Kruskal’s Gamma Coefficient of Rank Correlation (Calculation)
Chapter 6:16 Correlation & Regression3:21
§ Understanding Simple Regression
§ Understanding Multiple Regression
Chapter 6:17 Correlation & Regression3:26
§ Standard Error of Estimate
§ Coefficient of Determination
Chapter 6:18 Correlation & Regression5:39
§ Formulas of Simple Linear Regression
Chapter 6:19 Correlation & Regression14:33
§ Simple Linear Regression (Calculation)
§ Standard Error of Estimate (Calculation)
§ Coefficient of Determination (Calculation)
Chapter 6:20 Correlation & Regression3:07
§ Interpretation of results of Correlation Coefficient
Chapter 6:21 Correlation & Regression2:45
§ Multiple Regression
Chapter 6:22 Correlation & Regression22:48
Multiple Regression using Combined Correlation Method (Calculation)
Standard Error of estimate in Multiple Regression (Calculation)
Coefficient of Determination in Multiple Regression (Calculation)
Interpretation of Results
Tally With Excel Results

Chapter 7:1 Time Series Analysis1:06

§ Introduction of the Chapter
Chapter 7:2 Time Series Analysis3:22
§ Time Series Introduction
§ Historigram
§ Signal & Noise
Chapter 7:3 Time Series Analysis6:41
§ Uses of Time Series
§ Components of Time Series
§ Secular Trend
§ Seasonal Variation
§ Cyclical Variation
§ Irregular Variation
Chapter 7:4 Time Series Analysis3:48
§ Additive Model
§ Multiplicative Model
§ Measurement of Secular Trend
§ Free Hand Curve Method
Chapter 7:5 Time Series Analysis7:00
§ Measurement of Secular Trend (Method of Semi Average) Calculation
Chapter 7:6 Time Series Analysis7:10
§ Measurement of Secular Trend (Method of Semi Average) Calculation
Chapter 7:7 Time Series Analysis8:17
§ Measurement of Secular Trend (Method of Moving Average) Calculation
Chapter 7:8 Time Series Analysis7:18
§ Measurement of Secular Trend (Method of Least Square) Calculation
Chapter 7:9 Time Series Analysis5:14
§ Measurement of Secular Trend (Method of Least Square) Calculation
Chapter 7:10 Time Series Analysis4:40
§ Measurement of Secular Trend (Method of Least Square Changing Origin) Calculation
Chapter 7:11 Time Series Analysis3:01
§ Measurement of Secular Trend (Method of Least Square Changing Origin) Calculation
Chapter 7:12 Time Series Analysis7:35
§ Measurement of Seasonal Variation
§ Measurement of Seasonal Variation (Simple Average Method) Calculation
Chapter 7:13 Time Series Analysis14:56
§ Measurement of Seasonal Variation (Link Relative Method) Calculation
Chapter 7:14 Time Series Analysis9:47
§ Measurement of Seasonal Variation (Ratio to Moving Average Method) Calculation
Chapter 7:15 Time Series Analysis5:09
§ Measurement of Seasonal Variation (Ratio to Trend Method) Calculation
Chapter 7:16 Time Series Analysis6:04
Deseasonalization under Multiplicative Law
Chapter 7:17 Time Series Analysis12:33
Deseasonalization under Additive Law

Probability :17:23
Probability : 28:14
Probability : 35:31
Probability : 46:12
Explore practical probability by counting marbles, dice outcomes, and coin tosses, using sample spaces and events to compute simple probabilities for white, orange or red, and not red or blue.
Probability : 56:04
Probability : 69:38
Probability : 74:32
Probability : 89:20
Probability : 96:05
Explore the multiplicative laws of probability derived from conditional probability, including probability of intersection and the impact of independence, with an example of at least two players hitting six.
Probability : 109:35
Probability : 119:45
Probability : 125:40

Distribution: 16:05
Explore probability distribution concepts, including binomial and hypergeometric models, and define the random variable. Apply discrete probability function properties to a defective boards example with p(defective)=1/5.
Distribution : 29:19
Distribution : 39:04
Distribution : 43:55
Distribution : 54:51
Distribution : 69:21
Distribution : 713:22
Distribution : 813:55
Explore the hypergeometric distribution, where success probability changes in sampling without replacement. Derive its mean and variance and apply to real problems, comparing it with binomial distribution.

Requirements

There is no prerequisites

Description

Welcome to Complete Statistics for Business Analysis and Data Science + Practical questions!

This course has been designed from Scratch to Advanced level.

Fundamentals of Statistics
Learn about Statistics including important statistic business terms.
Presentation Of Data & Data Distribution, Measurements Of Central Tendency including Arithmetic Mean, Median, Mode, Harmonic Mean, Geometric Mean, Winsorized Mean, Trimmed Mean, Quartiles, Deciles & Percentiles.
Detailed Data Distribution Measures of Dispersion including absolute measures of dispersion and relative measures of dispersion , Range, Coefficient of Range, Quartile Deviation, Coefficient of Quartile Deviation, Mean Deviation through Mean, Median and Mode, Coefficient of Mean Deviation Median Deviation & Mode Deviation, Standard Deviation & Coefficient of Standard Deviation, Variance & Coefficient of Variation.
Learning Skewness and its measures & Kurtosis
Learn Correlation simple, Ranked and combined, Regression simple and Multiple.
Regression, including scatterplots, correlation coefficient
Numbers simple and composite including simple and chain index, weighted and un-weighted index & Consumer Price Index
Time series Analysis including semi average method, moving average, 4 quarter moving average centered, least square method, decomposition, ratio to moving average .
Probability
All with Practical Questions

YOU'LL ALSO GET:

Lifetime access to Complete Statistics for Business Analysis and Data Science
Friendly support in the Q&A section
Udemy Certificate of Completion available for download
30-day money back guarantee

Who this course is for:

People who want a career in Data Science
People who want a career in Business Intelligence
Business analysts
Business executives
Research Analysis
Individuals who are passionate about numbers and quant analysis
Anyone who wants to learn the subtleties of Statistics and how it is used in the business world
People who want to start learning statistics
People who want to learn the fundamentals of statistics

Students, I hope you will enjoy the course as much as I have wile designing the course. Students if you have any questions related to topics mentioned above kindly leave in the comments feedback section below.

Enroll Now to start the journey!

Best Regards

Iftikhar A.

Who this course is for:

All Students of Business & Finance (beginners & advanced) & every one who needs & manage to business well.
University Students Higher Education
Data Science
B Com Students
BBA Students
I Com Students

Complete Statistics For Business Analysis & Data Science

What you'll learn

Explore related topics

Course content

Introduction to Statistics13 lectures • 55min

Presentation of the Data9 lectures • 51min

Measures of Central Tendency23 lectures • 1hr 54min

Measures of Dispersion24 lectures • 2hr 3min

Index Numbers24 lectures • 1hr 57min

Correlation & Regression22 lectures • 2hr 28min

Time Series Analysis17 lectures • 1hr 54min

Section 8: Probability12 lectures • 1hr 28min

Section 9 : Distribution8 lectures • 1hr 10min

Section 10 : Sampling10 lectures • 1hr 17min

Requirements

Description

Who this course is for: