Probabilitas dan Statistika UI

Deskripsi

• Course Overview:

Statistics and probability has been known as applied mathematics which is widely used in collecting, organizing, presenting, interpreting and analyzing data to support valid conclusions. Furthermore, these conclusions will be used as recommendation in decision making. The course of Statistics and Probability is intended to give a basic ability for students to handle quantitative data and information. There are two stages that are delivered which is descriptive and inductive/ inference stages. Descriptive stage includes collecting, organizing, and presenting the data in a scientific manner. Then, inductive/inference stage includes the process of estimating and drawing conclusion based on available data and relations between variables. Hence, students are expected to apply their knowledge of statistics in conducting experiments in laboratory works/assignments as well as research studies in their final projects.

• Daftar Topik:
  • Introduction to Statistics and Data Analysis:
    • 1.1 Overview : Statistical Inference, Samples, Populations
    • 1.2 The role of Statistics and the Application in engineering
    • 1.3 The role of computer in Statistics
  • Descriptive Statistics:
    • 2.1. Discrete and Continuous Data
    • 2.2.Sampling Procedures, Collection & Organization of Data
    • 2.3.Graphical Methods and Data Description
    • 2.4.Measure of Location : The sample Mean & Median Exercise
    • 2.5.Measure of variability
  • Probability:
    • 3.1 Concept of Probability : sample space, events, counting sample points, probability of an event
    • 3.2 Probability of an Event
    • 3.3 Rules in Probability : additive, conditional, multiplicative, Bayes’ Rule
  • Random Variable:
    • 4.1 Concept of Random variable
    • 4.2 Discrete Probability Distribution
    • 4.3 Continuous Probability Distribution
    • 4.4 Probability Distribution with parameter
    • 4.5 Mean of Random Variable
    • 4.6 Variance of Random Variable 
  • Some of Discrete Probability Distribution:
    • 5.1 Discrete Uniform Distribution
    • 5.2 Binomial and Multinomial Distribution
    • 5.3 Hypergeometric Distribution
    • 5.4 Negative Binomial & Geometric Distribution
    • 5.5 Poisson Distribution
  • Some of Continuous Probability Distribution:
    • 6.1 Continuous Uniform Distribution
    • 6.2 Normal Distribution
    • 6.3 Gamma & Exponential Distribution
    • 6.4 Chi Square Distribution
    • 6.5 Weibull Distribution
    • 6.6 Lognormal Distribution
  • Sampling Distribution:
    • 7.1 Definition and Basic Concept
    • 7.2 Sampling Distribution
    • 7.3 Sampling Distribution of Means
    • 7.4 Sampling distribution of Proporsion
    • 7.5 Sampling Distribution of Variance
  • Estimation:
    • 8.1 Inferential Statistics
    • 8.2 Classical Method of estimation
    • 8.3 Single Sample : Estimating the Mean
    • 8.4 Two Samples : Estimating the difference between Two Means
    • 8.5 Single Sample : Estimating the Proportion
    • 8.6 Two samples : Estimating difference between proportion
    • 8.7 Single Sample : Estimating the Variance
    • 8.8 Two Samples : Estimating the Ration between two variance
    • 8.9 Sample Size Determination
  • One and Two-Sample Tests of Hypotheses:
    • 9.1. Statistical Hypotheses : A General Concept
    • 9.2. Testing a Statistical Hypotheses
    • 9.3. One or Two-tailed Tests
    • 9.4. P values for decision making in testing
    • 9.5. One – or Two samples : Test of Means
    • 9.6. One – or Two samples : Test of Proportion
    • 9.7. One – or Two samples : Test of Variance
    • 9.8. Chi square Test : Goodness of Fit, Independence, Homogenity, Several Proportion
    • 9.9. ANOVA
  • Simple Linear Regression:
    • 10.1. Introduction to Linear Regression
    • 10.2. Simple Linear Regression model
    • 10.3. Inferences concerning regression coefficients
    • 10.4. Simple Linear Correlation Analysis