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Topic outline
- Welcome Note video with Applications
Welcome Note video with Applications
Teacher's Information
Name: Dr. Md. Kamrul Hossain
Designation:
Associate Professor & Head
Department: General Educational Development
Desk: 806, AB 4, DSC
Contact Number:
01711069636
Mail:
kamrul.ged@diu.edu.bd
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For more information click here ....
Course Rationale
Statistics is the science that deals with the collection, description, analysis, interpretation, and presentation of data. Statistical methods in Statistics are applied in the solution of different problems in real life and help the researcher to make an effective decision that affect our daily lives. Statistical methods are used in development of planning, commerce, industry, business, formation of development policy, agricultural sector, social science etc. By studying this course, you will learn the fundamental knowledge about descriptive statistics and their applications.
Course Objectives
This course intends to provide the students with the
basic concepts of Statistics. Upon completion of this course, the student should be able -
1. to provide the students with a broad application of the statistical methods
along with probability theory.
2. to have a working knowledge of most of the statistical concepts.
3. to understand the
theoretical and practical knowledge of statistics.
4. to apply their statistical
knowledge and skills throughout their future studies.
Course Outcomes (CO’s)
Program Outcomes (PO’s)
Assessment Plan
Course Outline Or Course Delivery Plan
General Instruction for Assessment
1. Quiz - There will be 3 quiz. Average weight of the quiz for the course is 15%. Before mid term, you have to sit for Quiz 1 and 2.
2. Presentation - Presentation topic is open, that is you can choose any topic for presentation but there must be data. Prepared at least 3 minutes video and upload within due data in the presentation section. weight of presentation is 8%.
3. Assignment - There will be several assignment and activity and the weight is 5%.
4. For attending class, you will get 7% mark of the course.
Please contact in telegram/whatsapp in 01915641745
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Class 01 |
Class 02 |
Class 03 |
Class 04 |
Class 05 |
Class 06 |
Class 07 |
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- Lecture 1
Lecture 1
Introduction
At the very beginning of each semester, it needs to introduce myself to the students. It's also important to get a clear understanding of the students' abilities, performance, strengths, and weaknesses at the very beginning of the semester. As a result, it's easy to reach the students. So a nice introductory class help to buildup connection between students and teacher which make easier to continue the whole course.
When the students are starting a new course, they have some common questions like that,
a) Why they read this course?
b) Have any real-life application of this course?
I think these are very important questions and we must do fulfill their demand.
Hence, in my introductory class, I always try to buildup a clear understanding among the students and try to reach their emotion, their feelings, their strengths, and weaknesses. Clearly I try to show the necessity of this course and real-life application of this course.
So, I think at the very beginning of the semester, a good introductory class helps to make my course easier than the other classes.
- Lecture 2 -3 (Introduction)
Lecture 2 -3 (Introduction)
Introduction
You are thinking this a new course which you have never read. However, you have learn statistics as integrated part of mathematics during SSC and HSC. That is why we are going to recall few related terminology of Statistics.
Chapter Outcome
After reading this chapter, you should be able to:
1. Know
about the Statistics, Population, Sample, Variable
2. Classify variables into qualitative and quantitative
3. Importance of data and its use
Lesson Plan
- Discussion from a lecture slide
- Group work and also individual classwork
Lecture Related Supportive Materials:
PowerPoint Slide on This Lecture is HERE
The following video tutorial on this topic can be helpful
- Lecture 4 (Level of Measurement)
This topic
Lecture 4 (Level of Measurement)
Introduction
In this chapter we will learn to assign measurement to the variables.
Chapter Outcome
After reading this chapter, you should be able to:
1.
Know
about classification of level of measurement
2. Classify the variables to level of measurement
Lesson Plan:
- Discussion from a lecture slide
- Group work and also individual classwork
- Question and Answering
Lecture Related Supportive Materials:
PowerPoint Slide on This Lecture is HERE
Video Lecture on Level of Measurement
Video Lecture |
Supporting Document from External Source |
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- Data Presentation
Data Presentation
Lecture 5 & 6 (Data Presentation)
Introduction
In lecture 5 & 6, we will discuss and learn about construction of frequency distribution and drawing various types of charts and diagram based on type of data.
Learning Outcomes:
Know the appropriate tool for data presentation
Exploring
fact from data
Lesson Plan:
*Question and Answering Forum
*Discussion from a lecture slide
*Presentation
Lecture Related Supportive Materials:
PowerPoint Slide on This Lecture is Here: Lecture 1 & Lecture 2
Video Lecture on Data Presentation
Part 1
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Part 2
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- Lecture 7 and 8 (Measures of Central Tendency)
Lecture 7 and 8 (Measures of Central Tendency)
Introduction
In this class, I will discuss the different types of central tendency and what are the applications and importance in real life.
Chapter Outcome
After reading this chapter, you should be able to:
1.
Know
about central tendency
2.
Calculate central tendency
Lesson Plan
- Discussion from a lecture slide
- Group work and also individual classwork
Lecture Related Supportive Materials
Lecture Related Supportive Materials
Part 1 |
Part 2 |
Funny Video from External Source |
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- Lecture 9 (Measures of Location)
Lecture 9 (Measures of Location)
Introduction:
Summarizing data can help us understand them, especially when the number of data is large. Measures of location try to capture with a single number what is typical of the data. Without defining "representative" more precisely, it is not possible to get information from data.
Chapter Outcome:
After reading this chapter, you should be able to:
1.
Know
about calculate quartiles, deciles and percentiles
2.
Detect outlier
3. Draw boxplot
Lesson Plan:
- Discussion from a lecture slide
- Group work and also individual classwork
- Question and Answering
Lecture Related Supportive Materials:
Video Class Material
Part 1 |
Part 2 |
External Link |
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- Lecture 10 - 11 (Measures of Dispersion)
Lecture 10 - 11 (Measures of Dispersion)
Lecture 10 - 11 (Measures of Dispersion)
Introduction
Correlation measures the relationship among the variables. In this chapter, you will learn to calculate correlation between the variables. And you will know which method is appropriate for which type of data.
Objectives
Dispersion refers to measure the spreadness of a dataset. From this chapter you will learn to
Measure the absolute and relative measures of dispersion
Application of the different type of dispersion
Lesson Plan:
- Discussion from a lecture slide
- Group work and also individual classwork
- Question and Answering
Lecture Related Supportive Materials:
- Week 8-Module (Chapter 8):Regression Analysis
Week 8-Module (Chapter 8):Regression Analysis
Introduction
The shape of the data can be understood
by considering how the data points are distributed in the space. This
distribution can be categorized into Symmetrical Distribution. Two
numerical measures of shape give a more precise evaluation:
skewness tells you the amount and direction of
skew (departure from horizontal symmetry)
kurtosis tells you how tall and sharp the central
peak is, relative to a standard bell curve.
Learning Outcomes
•Measures
the Shape of the distribution
•Computation
process of Skewness and
Kurtosis
•Interpreting
Skewness and Kurtosis
Objectives
Understand the shape of distribution
Measure the lack
of symmetry of the distribution
For chapter materials, the learning material click HERE
- Correlation
Correlation
Introduction
Correlation measures the relationship among the variables. In this chapter, you will learn to
1. Identify the direction and strength of a linear correlation between two factors
2. Interpret the Pearson correlation coefficient and how to determine the coefficient
3. Draw scatter diagram and its explanation in aspect of correlation
Objectives
1. Measures the relationship among variables
2. Explanation of scatter diagram
Lesson Plan
1. Discussion from a lecture slide
2. Group work and also individual classwork
3. Question and Answering
Lecture Related Supportive Materials:
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Lecture 14- 15(Regression)
Introduction
At the end of the chapter students will learn
1. Distinguish between a independent variable and a dependent variable
2. Measuring influence of independent variable on dependent variable
3. Explaining a line from the view of regression
Objectives
1. Define the explanatory variable as the independent variable
2. Predict the value of the predict variable for a given value of the explanatory variable
Lesson Plan:
- Discussion from a lecture slide
- Group work and also individual classwork
Lecture Related Supportive Materials:
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Lecture 16- 18(Test of Hypothesis)
Introduction
Hypothesis is the statement about population. In every research, without testing hypothesis is not valid or worthy.
Objectives
1. Learn to set hypothesis
2. Know how to test hypothesis
Lesson Plan:
- Discussion from a lecture slide
- Groupwork and also individual classwork
- Question and Answering
Lecture Related Supportive Materials: HERE
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Introduction
Probability measures and quantifies "how likely" an event, related to these types of experiment, will happen. The value of a probability is a number between 0 and 1 inclusive. An event that cannot occur has a probability (of happening) equal to 0 and the probability of an event that is certain to occur has a probability equal to 1.
Lesson Plan:
- Discussion from a lecture slide
- Group work and also individual classwork
- Question and Answering
Lecture Related Supportive Materials:
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Introduction
A probability distribution is a list of all of the possible outcomes of a random variable along with their corresponding probability values.
Objectives
Know the application of probability distribution
Lesson Plan:
- Discussion from a lecture slide
- Groupwork and also individual classwork
- Question and Answering
Lecture Related Supportive Materials:
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What do you learn from DEV 532? How will you apply in real life? Discus in details.
- Quiz
Quiz
You are allow to use 25 there will be 2 attempts. Sequential movement
Content: i) Measures of Central Tendency
ii) Measures of Location
iii) Measures of Dispersion
iv) Shape of the Distribution
- Final Exam