STAT

ISTICS

Course Nr.: 0403111

Tafila Technical University

College of Business Dept. of Economics

1st Semester2017/2018

Lecturer: Dr. Veronika Alhanaqtah

Office Hours: Sunday, Tuesday, Thursday9:00 – 10:00(office 21)

Course Description:

Learning objectives:

The course introduces students to the discipline of Statistics as a science of understanding and analyzing data. The main focus is made on applied statistics which includes descriptive statistics and inferential statistics. Recognize the importance of data collection and

determine how they affect the scope of inference.

Use statistical packages in R-Studio to summarize data numerically and visually, and to perform data analysis.

Have a conceptual understanding of the unified nature of statistical inference.

Apply estimation and testing methods (confidence intervals and hypothesis tests) to analyze single variables and the relationship between two variables in order to understand natural phenomena and make data-based decisions.

Model and investigate relationships between two or more variables within a regression framework.

Complete practical assignments that employ simple statistical inference and modelling techniques.

Text Book: Introductory Statistics with Randomization and Simulation David M. Diez, Christopher D. Barr, Mine Catinkaya-Rundel, 1st Ed (2014)Lecture summaries and presentations: www.alveronika.wordpress.com Page Statistics

Software: R/R Studio (free resource) Official website: https://cran.r-project.org

Evalua

tion

1st Exam (20 Marks): November 12nd Exam (20 Marks): December 13

Laboratory Assignments (10 Marks)Final Exam (50 Marks)

Nr. Main Topic Weeks0 Introduction

What Statistics is aboutCourse requirements

1

1 Introduction to data1.1. Introductory concepts and vocabulary

1.1.1. Data Set. Unit of observation1.1.2. Variable. Variable types1.1.3. Online data libraries

1

1.2. Introduction to R and R Studio2 Descriptive statistics:

Univariate analysis2.1. One variable graphics and number summaries

2.1.1. Histogram. Symmetric and asymmetric distribution2.1.2. Box plot. Number summaries: minimum, 25th, 50th, 75th percentiles, maximum.

Outlier. Boundary fence2.2. Measures of central tendency and variability

2.2.1. Center: median, mean, mode2.2.2. Spread: range, inter-quartile range (IQR), standard deviation (SD), skewness,

kurtosis2.3. Transformation and standardizing

2.3.1. Mathematical transformations2.3.2. Standardizing (Z-score)

2.4. Normal distribution2.4.1. Bell-shaped distribution2.4.2. Empirical rule2.4.3. Standard normal probabilities2.4.4. Chebyshev’s theorem

2-6

First Exam

3 Descriptive statistics:Bivariate analyses3.1. Relationship between two categorical variables - Mosaic Plots and Contingency Tables3.2. Relationship between one categorical and one numeric variables – Side-by-side boxplots3.3. Relationship between two numeric variables – Correlation and Regression

7-9

4 Inferential statistics: foundations4.1. Simple linear regression4.2. The linear correlation coefficient4.3. Modeling linear relationships with randomness present4.4. The least squares regression line4.5. Statistical inferences about β2

4.6. The coefficient of determination4.7. Estimation and prediction

10-12

Second Exam5 Theory of probability

5.1. Numerical characteristics of random variables5.1.1. Types of averages: simple arithmetical average, weighted arithmetical average,

geometric average, chronological average, harmonic average5.1.2. Expected value5.1.3. Variance5.1.4. Standard deviation5.1.5. Covariance5.1.6. Covariance matrix5.1.7. Correlation coefficient

5.2. Events and probabilities (additional)5.3. Probability distributions (additional)

13-15

Laboratory Assignments in computer classes (R/R-Studio): in the course of a semesterFinal Exam