STATISTICAL METHODS |
This page is devoted to providing the needed learning resources by graduate students of Eastern Samar State University who are taking up a course on Statistics. The contents of this page are arranged in chronological order from the course information until the most recent topic of discussion.
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COURSE INFORMATIONDownload the course syllabus at the right for the complete information on the course, Statistical Methods.
The syllabus includes the Vision and Mission statement of the university, course content, grading criteria, and requirement details |
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1 Introduction to Statistics |
November 26th, First Session |
Statistics is derived from the Latin word status meaning “state”. Statistics is concerned with scientific methods for collecting, organizing, summarizing, presenting, analyzing, interpreting data and drawing conclusions based on that data. At the far right, you may download the slideshow presentation previously used in the class discussion. the file is saved in pdf.
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For this fraction of the course, graduate students who are taking up the course on Statistical Methods are expected to develop the following learning competencies:
1. Describe basic terms in statistics such as population, sample, parameter, and stastic. 2. Classify data as quantitative or qualitative, discrete or continuous, and according to scales of measure. 3. Differentiate methods of data presentation. 4. Construct Frequency Distribution Tables. 5. Represent frequency distribution tables through histograms and frequency polygons. |
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LEARNING TASK 1: The Nature of Data and Frequency Distribution Tables
Download the document (File No. 1) and have it printed on a letter-sized paper. Use the actual printout as answer sheet and have this submitted during the next regular class session on December 10th. You may opt to computerize your answers. In that case, download File No. 2 instead which is the same document but is editable in MS Word.
To address the confusion on class size and class interval. Note that the Sturge's formula is used to determine the number of intervals. To obtain the sample size, divide the Range by the result of the Sturge's formula. |
File No. 1 (PDF)
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File No. 2 (Word Document)
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Additional Resources: FREQUENCY POLYGONS, HISTOGRAMS, STEM-AND-LEAF PLOTS
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2 Measures of Central TendencyFor this fraction of the course, graduate students who are taking up the course on Statistical Methods are expected to develop the following learning competencies:
(on Data Presentation) 1. Construct histograms, frequency polygons and ogives based on a given frequency distribution table for grouped data. 2. Create a stem-and-leaf plot based on a given raw data 3. Explain the advantage of using stem-and-leaf plot over a frequency distribution table and vice versa. (on Summation and Measures of Central Tendency) 1. Describe the concept of summation and compute for the sum of a set of data expressed through summation notation 2. Differentiate the three common measures of central tendency 3. Compute for the mean, median, and mode of both ungrouped and grouped data. |
December 10th, Second Session |
LEARNING TASK 2: Summation Notation and Measures of Central Tendency
This second learning task is focused on supplementing your understanding of summation and the measures of central tendency: the mean, median, and mode.
Parts of the document will also prompt you to present raw and grouped data through stem-and-leaf plots, histograms, and frequency polygons. You may submit a scanned copy of your answer sheet to my email, [email protected], or submit the actual paper during the next session on December 17th. For questions, please send me a private message. |
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3 Measures of Position and Variability |
January 7th, 2017, Third Session |
For this fraction of the course, graduate students who are taking up the course on Statistical Methods are expected to develop the following learning competencies:
(on Measures of Position) 1.Describe the three types of quantiles. 2.Interpret the position of a given score based on its quantile rank. 3.Compute for a specific quartile, or decile of a given raw set of data and the percentile of a grouped data. (on Measures of Variability) 1.Explain the concept of variability as defined in statistics. 2.Compare the most common measures of variability by stating the advantages and disadvantages of using each. 3.Compute for the range, variance, and standard deviation of a given set of raw or grouped data. |
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LEARNING TASK 3: Measures of Position and Variability
The purpose that the third learning task serves is to assess your understanding of the common measures of position and measures of variability.
The document is composed of two parts - one for each chapter. Download the document at the right. If you continue to experience difficulty in working with Scribd, another download link is at the bottom. Click this link instead. Make sure to include all your solutions on the paper that you submit. Submission is expected on January 21st before the start of the midterm examination. All other requirements prior to this must also be submitted. |
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4 The Normal Distribution
For this fraction of the course, graduate students who are taking up the course on Statistical Methods are expected to develop the following learning competencies:
1.Describe normal distributions through the properties of the normal curve. 2.Convert raw scores into standard (z) scores. 3.Compute for the area under the normal curve. 4.Interpret areas under the normal curves as probabilities. 5.Define skewness and kurtosis. 6.Describe a distribution in terms of its skewness and kurtosis based on its curve |
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5 Hypothesis Testing
For this fraction of the course, graduate students who are taking up the course on Statistical Methods are expected to develop the following learning competencies:
1.Discuss in detail hypothesis testing. 2.Define important terms related to hypothesis testing (e.i. null and alternative hypotheses, test statistic, critical value and region, type of test, level of significance) 3.Differentiate Types I and II errors in hypothesis testing. 4.Describe the steps in hypothesis testing. 5.Test hypotheses using the traditional method. |
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LEARNING TASK 4: Hypothesis Testing
This fourth learning task aims to provide you with the experience of employing hypothesis testing using various test statistic. It is composed of ten items of varying difficulties.
Your task is to answer all items using the traditional method of hypothesis testing. The document at the right of this text offers a summary and examples of the test statistic that you will need to use to complete the task. |
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6 Correlation Analysis
Learner's Module on Correlation
This module provides a comparative discussion of the most common correlation coefficients used in Statistics.
The objective of the module is not only to define and provide examples for each coefficient but also to describe when each type is appropriate to use based on the type of data that are being tested for significant relationship. This will be the focus of discussion for the class on March 18th. Download Learning Task 5 below. |
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