computer skills – 2 (c++)€¦  · web viewstatistics course nr.: 0403111 tafila technical...

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Course Nr.: 0403111 Tafila Technical University College of Business Dept. of Economics 2 nd Semester 2016/2017 Lecturer: Dr. Veronika Alhanaqtah Office Hours: Monday, Wednesday 9:30 – 11:00 (office 347) Course Description: The course introduces students to the discipline of Statistics as a science of understanding and analyzing data. The goals of this course are as follows: 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, 1 st 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

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Page 1: Computer Skills – 2 (C++)€¦  · Web viewSTATISTICS Course Nr.: 0403111 Tafila Technical University. College of Business . Dept. of Economics. 2nd Semester. 2016/2017. Lecturer:

STAT

ISTICS

Course Nr.: 0403111

Tafila Technical University

College of Business Dept. of Economics

2nd Semester2016/2017

Lecturer: Dr. Veronika Alhanaqtah

Office Hours: Monday, Wednesday9:30 – 11:00(office 347)

Course Description:

The course introduces students to the discipline of Statistics as a science of understanding and analyzing data. The goals of this course are as follows: 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): March 92nd Exam (20 Marks): April 20

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

Nr. Main Topic Sub-Topic0 Introduction What Statistics is about

Course requirements

1 Introduction to data 1.1. Introductory concepts and vocabulary1.1.1. Data Set. Unit of observation1.1.2. Variable. Variable types1.1.3. Online data libraries

2 Descriptive statistics: 2.1. One variable graphics and number summaries

Page 2: Computer Skills – 2 (C++)€¦  · Web viewSTATISTICS Course Nr.: 0403111 Tafila Technical University. College of Business . Dept. of Economics. 2nd Semester. 2016/2017. Lecturer:

Univariate analysis 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

First Exam

3 Descriptive statistics:Bivariate analyses

3.1. Relationship between two categorical variables - Mosaic Plots and Contingency Tables

3.2. Relationship between one categorical and one numeric variables – Side-by-side boxplots

3.3. Relationship between two numeric variables – Correlation and Regression

4 Inferential statistics: foundations 4.1. 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

Second Exam

5 Theory of probability 5.1. Numerical characteristics of random variables5.1.1. Types of averages

Simple arithmetical averageWeighted arithmetical averageGeometric averageChronological averageHarmonic average

5.1.2. 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)

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