• Category: Web & Mobile Development
• Product Type: Online Course

Section 1: Understanding R 1 Basics of R 2 Basic R Functions 3 Data Types 4 Recycling Rule 5 Special Numerical Values 6 Parallel Summary Functions 7 Logical Conjunctions 8 Pasting Strings together 9 Type Coercion 10 Array & Matrix 11 Factor 12 Repository & Packages 13 Installing a Package 14 Importing Data 15 Importing Data SPSS 16 Working with Data 17 Data Aggregation   Section 2: Data Manipulation & Statistics Basics 18 Data Manipulation & Statistics Basics 19 Merging 20 Data Creation 21 Merge Example 22 What is Statistics 23 Variables 24 Quantiles 25 Calculating Variance 26 Calculating Covariance 27 Cumulative Frequency 28 Library (mass) 29 Head (faithful) 30 Scatter Plot 31 Control Flow   Section 3: Statistics, Probability & Distribution 32 Statistics, Probability & Distribution 33 Random Variable 34 Random Example 35 Discrete Example 36 Practice problem 37 Continuous Case 38 Exponential Distribution Practice Problem 39 Expected Value 40 Gambling Example 41 Deal or no deal 42 Distribution details 43 Binomial Distribution continued 44 Expected Value from Binomial 45 Uniform Random Variables 46 Probability distributions examples 47 Probability distributions examples continued   Section 4: Business Analytics using R 48 Business Analytics using R 49 Normal PDF 50 What is Normal, Not Normal 51 SAT Example 52 Example- Birth Weights 53 dNorm, pNorm, qNorm 54 Understanding Estimation 55 Properties of Good Estimators 56 Central Limit Theorem 57 Kurtosis 58 Constructing Central Limit Theorem 59 Confidence Intervals for the Mean 60 Confidence Intervals Examples 61 Computer Lab Example 62 t-distribution 63 t-distribution continued   Section 5: Examples, Testing & Forecasting 64 R Examples 65 Standard error of the mean 66 Downloading the Package 67 Sample Differences 68 Hypothesis Generation & Testing 69 Hypothesis Testing 70 One sided P Value 71 Power & Sample Size 72 Testing Hypothesis using R 73 Calculating the Z value 74 Lower Tail proportion of population proportion 75 Forecasting 76 Time Series Analysis Applications 77 Approaches to Forecasting 78 Observation Components 79 Traditional Approaches 80 Double Exponentional Smoothing 81 ARIMA Steps 82 Forecasting Performance 83 Univariate ARIMA   Section 6: Understanding Visualizations 84 R Visualization 85 Why Visualize 86 Overlaying Plots 87 Graphs representation of Data 88 Graphs representation of Data continued 89 Advanced Graphs 90 Bubble Charts 91 Anova 92 Concept of effect 93 Estimate of Treatment effect 94 Factorial Anova 95 Regression 96 Regression Model 97 Linear Relationship 98 Output of Regression Model ... Read More