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To introduce the student to some special data- terms which are widely used in statistics. |
a1 |
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To understand the descriptive analysis to the data by using the appropriate descriptive measures. |
a2 |
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To study the type and degree of correlation between two variables and their regression equation. |
a3 |
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To know the axioms of the theory of probability and how to find probabilities. |
a4 |
b. Mental skills
To help student of having appropriate statistical skills:
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to be able to classify data and to graphically represent it |
b1 |
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to be able to measures of central tendency and dispersion and other concepts such as kurtosis and skewness. |
b2 |
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to be able to detect the linear relation of two variables and to find the value of correlation and to explain it. |
b3 |
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to be able to obtain the sample space and calculate the probabilities. |
b4 |
c. Practical & professional skills
After the completion of the course a student supposed to be able to:
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To recognize types of data and how to present and summarize data. |
c1 |
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To select the appropriate measure of central tendency, dispersion, kurtosis and skewness. |
c2 |
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Determine the concept of correlation and its relation with regression. |
c3 |
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To use the numeration methods to calculate probabilities. |
c4 |
d. Generic and transferable skills
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Students to be able to work as a team and that to treat data sets. |
d1 |
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Students to be able to use calculators and other tools to analyze data. |
d2 |
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Students to be able to gain skills of describe and represent data. |
d3 |
References
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place |
writer |
Edition |
Publisher |
Reference Type |
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Class teacher notes |
Course Notes |
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University selling store |
العماري & العجيلي |
2000 |
الاحصاء والاحتمالات النظرية والتطبيق |
Text book |
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|
Peter Dalgaard |
2nd |
Introductory Statistics with R |
Sub-Text book |
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Journals |
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Internet cites |
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others |
Course Contents:
· Introduction to Statistics
· Probability: Sample Space – Events – Counting Sample Points (Permutations and Combinations) – definition of Probability – Conditional Probability – Independence – Baye’s Theorem.
· Random Variables and Probability Distributions: Concept of Random variable – Probability Function of Random Variable (Discrete and Continuous).
· Mathematical Expectation: Definition of Expectation – Means and Variances of Linear Combinations of Random Variables.
· Special Distributions: Binomial – Poisson – Normal and t-distributions.
· Sampling: Concept of Sampling – Sampling Distribution of Sample Mean – Central Limit Theorem – Sampling Distribution of Sample Proportion
· Estimation: Statistical Inference (Basic Concept of Point and Interval Estimation) – Estimation of Population Mean, Population Proportion.
Testing of Hypotheses: Concept of Statistical Hypotheses – Basic Steps of Testing a Hypothesis Concerning: One Population Mean, Population Proportion .