Computer Skills – 2 (C++)



|STATISTICS |Course Nr.: |0403111 |[pic] |

| | | |Tafila Technical University |

| | | |College of Business |

| | | |Dept. of Economics |

| | | |1st Semester |

| | | |2017/2018 |

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| | | |Lecturer: |

| | | |Dr. Veronika Alhanaqtah |

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| | | |Office Hours: |

| | | |Sunday, Tuesday, Thursday |

| | | |9:00 – 10:00 |

| | | |(office 21) |

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| |Course Description: |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.| |

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| |Learning objectives: |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. | |

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| |Text Book: |Introductory Statistics with Randomization and Simulation | |

| | |David M. Diez, Christopher D. Barr, Mine Catinkaya-Rundel, 1st Ed (2014) | |

| | |Lecture summaries and presentations: alveronika. | |

| | |Page Statistics | |

| |Software: |R/R Studio (free resource) | |

| | |Official website: | |

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| |Evaluation |1st Exam (20 Marks): November 1 | | |

| | |2nd Exam (20 Marks): December 13 | | |

| | |Laboratory Assignments (10 Marks) | | |

| | |Final Exam (50 Marks) | | |

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|Nr. |Main Topic |Weeks |

|0 |Introduction |1 |

| |What Statistics is about | |

| |Course requirements | |

|1 |Introduction to data |1 |

| |Introductory concepts and vocabulary | |

| |Data Set. Unit of observation | |

| |Variable. Variable types | |

| |Online data libraries | |

| |Introduction to R and R Studio | |

|2 |Descriptive statistics: |2-6 |

| |Univariate analysis | |

| |One variable graphics and number summaries | |

| |Histogram. Symmetric and asymmetric distribution | |

| |Box plot. Number summaries: minimum, 25th, 50th, 75th percentiles, maximum. Outlier. Boundary fence | |

| |Measures of central tendency and variability | |

| |Center: median, mean, mode | |

| |Spread: range, inter-quartile range (IQR), standard deviation (SD), skewness, kurtosis | |

| |Transformation and standardizing | |

| |Mathematical transformations | |

| |Standardizing (Z-score) | |

| |Normal distribution | |

| |Bell-shaped distribution | |

| |Empirical rule | |

| |Standard normal probabilities | |

| |Chebyshev’s theorem | |

|First Exam |

|3 |Descriptive statistics: |7-9 |

| |Bivariate analyses | |

| |Relationship between two categorical variables - Mosaic Plots and Contingency Tables | |

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

| |Relationship between two numeric variables – Correlation and Regression | |

|4 |Inferential statistics: foundations |10-12 |

| |Simple linear regression | |

| |The linear correlation coefficient | |

| |Modeling linear relationships with randomness present | |

| |The least squares regression line | |

| |Statistical inferences about β2 | |

| |The coefficient of determination | |

| |Estimation and prediction | |

|Second Exam |

|5 |Theory of probability |13-15 |

| |5.1. Numerical characteristics of random variables | |

| |5.1.1. Types of averages: simple arithmetical average, weighted arithmetical average, geometric average, chronological average, | |

| |harmonic average | |

| |5.1.2. Expected value | |

| |5.1.3. Variance | |

| |5.1.4. Standard deviation | |

| |5.1.5. Covariance | |

| |5.1.6. Covariance matrix | |

| |5.1.7. 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 semester |

|Final Exam |

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