وب سایت تخصصی شرکت فرین
دسته بندی دوره ها

Statistics for Data Science and Business Analysis

سرفصل های دوره

Mastering Statistics Fundamentals using R Programming


1 - Introduction
  • 1 - Introduction
  • 2 - What you will learn in this tutorial.html

  • 2 - R Programming
  • 3 - Why Do We Need R
  • 4 - What Is R and R Studio
  • 5 - R Installation
  • 6 - RStudio Installation
  • 7 - R Studio Interface Console and Help Tab
  • 8 - R Studio Interface File Packages Plot and Environment Tabs
  • 9 - Create a New Project in R
  • 10 - Download Code and Data Files for This Project
  • 10 - RScriptAndData.rar
  • 11 - R Packages
  • 12 - Install a Package in R
  • 13 - Load a Package in R
  • 14 - R Data Sets
  • 15 - Broom in R Studio
  • 16 - Get the Feel of the Data
  • 17 - Get the Feel of the Data View
  • 18 - Get the Feel of the Data glimpse
  • 19 - Types of Variables in R
  • 20 - Types of Variables in R Integers
  • 21 - Types of Variables in R Numerics
  • 22 - Types of Variables in R Factors or Categorical Variables
  • 23 - Types of Variables in R Types of Factors or Categorical Variables
  • 24 - Errors Warnings and Messages
  • 25 - Error Warning and Messages Errors
  • 26 - Error Warning and Messages Information Messages
  • 27 - Error Warning and Messages Warning Messages
  • 28 - Error Warning and Messages A Quick Recap

  • 3 - Subjects in the Population
  • 29 - Subjects in a Population

  • 4 - Statistical Questions
  • 30 - Statistical Questions
  • 31 - Types of Statistical Questions
  • 32 - Descriptive Questions
  • 33 - Comparative Questions
  • 34 - Relationship Questions
  • 35 - Causal Questions
  • 36 - Predictive Questions

  • 5 - Types of Data
  • 37 - Types of Data
  • 38 - Categorical Data
  • 39 - Nominal Categorical Data
  • 40 - Ordinal Categorical Data
  • 41 - Dichotomous Categorical Data
  • 42 - Quantitative Data
  • 43 - Discrete Quantitative Data
  • 44 - Continuous Quantitative Data
  • 45 - Why It Is Important to Classify Variables

  • 6 - Descriptive and Inferential Statistics
  • 46 - Descriptive and Inferential Statistics
  • 47 - Descriptive Statistics
  • 48 - General Social Survey
  • 49 - Real World Example of Descriptive Statistics GSS Survey
  • 50 - Descriptive Statistics for the Entire Population
  • 51 - Inferential Statistics
  • 52 - Sample Statistics and Population Parameters.html

  • 7 - Distribution of a Variable and Frequency Table
  • 53 - Distribution of a variable and Frequency table
  • 54 - Distribution of a Categorical Variable
  • 55 - Frequency Table for Categorical Variables
  • 56 - Understanding Relative Frequency Proportions and Percentages
  • 57 - Distribution of Quantitative Variables
  • 58 - Frequency Table for Discrete Quantitative Variables
  • 59 - Frequency table for discrete Var Hours Per Day Watching TV Limited Outcomes
  • 60 - Frequency table for discrete Var Ideal Number of Kids Limited Outcomes
  • 61 - Frequency table for discrete Var Math Exam Scores Wide Range of Outcomes
  • 62 - Frequency Table Continuous Quantitative Variables
  • 63 - Frequency Table for Continuous Variables Age in Census
  • 64 - Calculate Proportion and Percentages in Excel
  • 65 - Task 1 Frequency Table for Discrete Quantitative Variable in Excel
  • 66 - Task 2 Frequency Table for Categorical Variable in Excel
  • 67 - Titanic Dataset
  • 68 - Loading Titanic Data Set from Excel into R
  • 69 - Getting to Know the Titanic Dataset Exploring Variables
  • 70 - Frequency Table for Categorical Variables in R
  • 71 - Proportions and Percentages in Frequency Table in R
  • 72 - Pipe Operator
  • 73 - Discrete Data
  • 74 - General Social Survey Number of Kids
  • 75 - Recreating GSS Survey Data in Excel Ideal Number of Kids
  • 76 - Frequency Table for Discrete Data 1 Loading Number of Kids Data in R
  • 77 - Frequency Table for Discrete Data 2 Creating a Frequency Table
  • 78 - Frequency Table for Continuous Data 1 Loading Titanic Data In R
  • 79 - Frequency Table for Continuous Data 2 Calculating Range
  • 80 - Frequency Table for Continuous Data 3 Grouping Passengers by Age Group
  • 81 - Frequency Table for Continuous Data 4 LeftClosed and RightOpen Intervals
  • 82 - Frequency Table for Continuous Data 5 Creating a Frequency Table
  • 83 - Frequency Table for Continuous Data 6 Missing Values NAs

  • 8 - Visualizing the Distribution of a Variable Using Graphs
  • 84 - Graphs
  • 85 - Bar Graph
  • 86 - Pie Chart
  • 87 - Pie Chart in R
  • 88 - Bar graph or Pie chart Article.html
  • 89 - Histogram for a Discrete Variable
  • 90 - Histogram for a Discrete Variable in R
  • 91 - Histogram for a Continuous Variable
  • 92 - Histogram for a Continuous Variable
  • 93 - Histogram for a Continuous Var LeftClosed RightOpen Adjusting Intervals
  • 94 - Histogram for a Continuous Var Dealing with Missing Values
  • 95 - Histogram for a Continuous Var Setting Interval Lengths in a Histogram

  • 9 - The Shape of the Distribution
  • 96 - The Shape of a Distribution
  • 97 - Unimodal Distribution
  • 98 - Symmetric Distribution
  • 99 - Symmetric Distribution of Male Height An Example
  • 100 - Simulating Hypothetical Normal Distribution in R Male Heights
  • 101 - Symmetric Distribution Histogram in R
  • 102 - Skewed Distributions
  • 103 - LeftSkewed Distribution
  • 104 - LeftSkewed Distribution Histogram in R
  • 105 - RightSkewed Distribution
  • 106 - RightSkewed Distribution Histogram in R
  • 107 - Bimodal Distributions
  • 108 - Histogram for Bimodal Distribution
  • 109 - Another Example of Bimodal Distribution
  • 110 - Histogram for Bimodal Distribution 2
  • 111 - Uniform Distribution
  • 112 - Simulating Hypothetical Uniform Distribution in R Dice Output
  • 113 - Histogram for Uniform Distribution

  • 10 - Center of Quantitative Data
  • 114 - Center of Quantitative Data
  • 115 - Mode
  • 116 - Mode in Symmetric Discrete Distribution
  • 117 - Mode in Left Skewed Discrete Distribution
  • 118 - Mode in Right Skewed Discrete Distribution
  • 119 - Mode in Uniform Discrete Distribution
  • 120 - Mode in Categorical Variables
  • 121 - Mean
  • 122 - Calculating Mean in Excel
  • 123 - Impact of Outliers on the Mean
  • 124 - Formula for the MeanArticle.html
  • 125 - Compute Population Mean in R
  • 126 - Compute Sample Mean in R Part 1
  • 127 - Compute Sample Mean in R Part 2
  • 128 - Median
  • 129 - Impact of Outliers on the Median
  • 130 - Formula for Median Article.html
  • 131 - Compute Population Median in R
  • 132 - Compute Sample Median in R
  • 133 - Outliers and Skewed Distributions Article.html
  • 134 - Mean and Median in Symmetric Distribution
  • 135 - Mean and Median in Symmetric Distribution In R
  • 136 - Mean Median in Skewed Distribution Article.html
  • 137 - Mean Median in Right Skewed Distribution In R
  • 138 - Mean Median in Left Skewed Distribution In R
  • 139 - The Mean or Median Article.html

  • 11 - Measuring the Variability of Quantitative Data
  • 140 - What is the Variability
  • 141 - Range
  • 142 - Standard Deviation
  • 143 - Compute Standard Deviation Manually in ExcelPart 1
  • 144 - Compute Standard Deviation Manually in ExcelPart 2
  • 145 - Formula for Population Standard Deviation Article.html
  • 146 - Formula for the Sample Standard Deviation Article.html
  • 147 - Population Standard Deviation In R
  • 148 - Sample Standard Deviation In R
  • 149 - Sample Standard Deviation Formula Recap
  • 150 - Calculate Standard Deviation Manually in R Using n1 Part 1
  • 151 - Calculate Standard Deviation Manually in R Using n1 Part 2
  • 152 - Sample Standard Deviation vs Population Standard Deviation Article.html
  • 153 - n versus n1 Mathematically Article.html
  • 154 - Hypothetical Normal Distribution
  • 155 - Hypothetical Normal Distribution In R
  • 156 - ZScore Article.html

  • 12 - Empirical Rule
  • 157 - Empirical Rule
  • 158 - Empirical Rule in R Part 1
  • 159 - Empirical Rule in R Part 2
  • 160 - Understanding Data Distribution with the Empirical Rule
  • 161 - Outliers in Normal Distributions Article.html
  • 162 - Plausible Value of Standard Deviation Article.html

  • 13 - Percentiles and Quartiles
  • 163 - Percentiles and Quartiles
  • 164 - Percentiles and Quartiles in R
  • 165 - RealLife Usage of Percentiles Growth Charts
  • 166 - RealLife Usage of Percentiles SAT Exams
  • 167 - Making Sense of SAT Scores The Scaling Process Simplified Article.html
  • 168 - 5Number Summary Using Quartiles Article.html
  • 169 - Measuring Variability Using Interquartile Range IQR
  • 170 - Identifying Outliers Using Interquartile Range IQR.html
  • 171 - Boxplot in R
  • 172 - Creating SidebySide Box Plots
  • 173 - Comparing Two Distributions Using Box Plots

  • 14 - Relationship Between Variables
  • 174 - Relationship Between Variables
  • 175 - Response and Explanatory Variables Article.html
  • 176 - Types of Relationship
  • 177 - Relationship Between Two Categorical Variables
  • 178 - Contingency Table
  • 179 - Contingency Table In R
  • 180 - Stacked Bar Plot Article.html
  • 181 - Stacked Bar Plot In R
  • 182 - Relationship between Categorical and Quantitative Variables
  • 183 - Relationship between Two Quantitative Variables
  • 184 - Positive Relationship Article.html
  • 185 - Negative Relationship Article.html
  • 186 - No Relationship Article.html
  • 187 - Scatterplot in R
  • 188 - Correlation Article.html
  • 189 - Correlation In R

  • 15 - Summary
  • 190 - Summary.html
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    شناسه: 37959
    حجم: 1835 مگابایت
    مدت زمان: 322 دقیقه
    تاریخ انتشار: 6 تیر 1403
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