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Elementary Statistics – STAT. 111
Course Title English Code /No contact hours / week C.H.
Th. Pr. Tr. TCH
Statistics for Theoretical Dis-
ciplines STAT 111 3 - 3
Pre-requisites: None
Brief contents, to be posted in university site and documents(4-5 lines):
This course is designed to teach students how to use a broad base of statistical methods and concepts to organize, analyze, and interpret hypotheses developed in various applica- tions. This course consists of three main parts:
1. Data analysis and description 2. Probability and random variables 3. Inferential statistics
Objectives :
Main goal for this class is to familiarize students with the various techniques of statistical analyses that are utilized in different disciplines. Emphasis will be on the basic concepts and their meaning, as well as their applications and interpretation.
Course Outcomes :
The successful completion of this course will enable the students to
Chapter 1: Introduction to Statistics
After completing this chapter, you should be able to 1. Demonstrate knowledge of statistical terms.
2. Differentiate between the two branches of statistics.
3. Identify types of data.
4. Identify the measurement level for each variable.
5. Identify the four basic sampling techniques.
6. Explain the difference between an observational and an experimental study.
7. Explain the importance of computers and calculators in statistics.
Chapter 2: Displaying and Organizing Data
After completing this chapter, you should be able to 1. Organize data using frequency distributions.
2. Represent data in frequency distributions graphically using histograms, frequency polygons, and frequency curve.
3. Represent data using bar chart, time series graphs, and pie graphs.
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Chapter 3: Descriptive Statistical Measures :
After completing this chapter, you should be able to
1. Summarize data using measures of central tendency, such as the mean, median, and mode.
2. Describe data using measures of variation, such as the range, variance, and standard deviation.
3. Identify the distribution shapes, using skewness measure.
Chapter 4: Correlation & Simple Linear Regression :
After completing this chapter, you should be able to 1. Draw a scatter plot for a set of ordered pairs.
2. Compute the Pearson linear correlation coefficient.
3. Compute the Spearman rank correlation coefficient.
4. Compute the Point Biserial correlation coefficient 5. Compute the Phi correlation coefficient
6. Compute the equation of the regression line.
Chapter 5: Some Applications in Descriptive Statistics :
After completing this chapter, you should be able to 1. Biostatistics.
2. Compute index numbers.
Chapter 6: Introduction to Probability and Probability Distribution :
After completing this chapter, you should be able to
1. Determine sample spaces and find the probability of an event, using classical probability or empirical probability.
2. Find the probability of compound events, using the addition rules.
3. Find the probability of compound events, using the multiplication rules.
4. Find the conditional probability of an event.
5. Construct a probability distribution for a random variable.
6. Find the mean, variance, standard deviation، and expected value for a discrete random variable.
7. Find the exact probability for X successes in n trials of a binomial experiment.
8. Find the mean, variance, and standard deviation for the variable of a binomial distribution.
Chapter 7: The Normal Distribution :
After completing this chapter, you should be able to 1. Identify distributions as symmetric or skewed.
2. Identify the properties of a normal distribution.
3. Find the area under the standard normal distribution, given various z values.
4. Find probabilities for a normally distributed variable by transforming it into a standard normal variable.
5. Find specific data values for given percentages, using the standard normal distribution.
6. Use the central limit theorem to solve problems involving sample means for large samples.
Chapter 8: Estimation and Hypotheses Testing
After completing this chapter, you should be able to 1. Find the confidant intervals for the mean.
2. Hypothesis testing for the mean large samples.
3. Using P-value for hypothesis testing.
4. Chi-square testing.
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Text book :
Introduction to Statistics for theoretical disciplines, Author(s): Department of statistics, King Abdulaziz University, Publisher: Al-Khwarizm (2013)
Other Information Resources :
http://amadaghistani.kau.edu.sa/Pages-stat111ar.aspx
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Title Chapter
Lecture (.S.T.) Lecture
(S.M.W) Week
Orientation 1
1
1 Introduction
CH1 2 2
Descriptive and Inferential Statistics Variables and Types of Data 3
Data Collection and Sampling Techniques 1 1
2
Observational and Experimental Studies Introduction
CH2
2 Organizing Data
2 Categorical frequency distributions
3 Ungrouped frequency distributions
Grouped frequency distributions 1 1
3 2
Histograms-Frequency Polygons-and Curves 2
3 Other Types of Graphs
Introduction - Measures of Central Tendency CH3
1 1
4 2
Measures of Variation 2
3
Measures of skewness 1 1
5
Introduction
CH4
Scatter Plots and Pearson Correlation 2
The Spearman Rank Correlation Coefficient (no ties)
2 3
Point Biserial and Phi Correlation Coefficient - Regression
1 1
6 Review
(Solve Exercises-Old Exams) 2 ----
2 3
Exam 1 Week Off
Time table for distributing theoretical/practical course contents :
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Title Chapter
Lecture (.S.T.) Lecture
(S.M.W) Week
Biostatistics CH5
1 1
7 Index number
Sample Spaces and Probability
CH6 2 2
The Addition Rules for Probability 3
The Multiplication Rules 1 1
8
Probability Distributions
2 Mean-Variance-Standard
Deviation 2
3
The Binomial Distribution 1
1
9 Review
(Solve Exercises-Old Exams) ----
2 2 3 Exam 2
Normal Distributions CH7
1 1
11 2 2
The Central Limit Theorem (Distribution of Sample Means)
3
confidant intervals for the mean CH8
1 1
12 Hypothesis testing for the mean large samples
2 2
P-value for hypothesis testing - Chi-square testing
3
Review
(Solve Exercises-Old Exams) 1 ----
1
13 2
2 3
Final