Section outline

  • Welcome to STA-201 (Statistics for Business Decisions)

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    Statistics is the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample.

    ‘Statistics in Business’ applies statistical methods in the business context in order to address business-related questions and help make evidence-based decisions. The main objective of Business Statistics is to make inferences about certain characteristics of a population in the business domain whether the population is people, objects, or collections of information.

    Course Objectives: Upon completion of this course, the student should be able to-

    • Understand basic theoretical and applied principles of statistics 
    • Communicate key statistical concepts to non-statisticians
    • Apply statistical knowledge and skills throughout their future studies and careers

    Course Instructor

    Muhammad Mustafa Shakil
    Lecturer
    Department of Innovation & Entrepreneurship
    Daffodil International University
    Email: muhammad.die@diu.edu.bd

  • Topic-1

    Statistics Illustrations and Clipart. 213,657 Statistics royalty free illustrations, and drawings available to search from thousands of stock vector EPS clip art graphic designers.

    • Define statistics, their use & types, Population, Sample, Define variables and types of it

      Lecture Objectives:

      (a) Explain what statistics is.

      (b) Understand the ways that statistics are used.

      (c) Know the differences between descriptive and inferential statistics.

      (d) Understand the differences between a sample and a population.

      (e) Understand Why to take a sample instead of studying every member of the population.

      (f) Explain what is variable

      (g) Understand various types of variables

      (h) Understand the difference between qualitative and quantitative variable

      (i) Understand Discrete and Continuous variable 

      (j) Understand the difference between Discrete and Continuous variable 

      Lecture Contents:

      (a) Statistics.

      (b) Descriptive and inferential statistics.

      (c) Population

      (d) Sample

      (e) Variable

      (f) Qualitative and Quantitative variable

      (g) Discrete and Continuous Variable 

    • resource icon
      Introduction to Statistics File

      Students can learn about descriptive statistics , inferential statistics, sample and population.

    • resource icon
      Statistics-An Introduction File

      Students can get about introductory ideas of statistics.

    • choice icon
      Discrete or Continuous variable? Choice
      Students must
      Mark as done
    • forum icon
      Discuss the importance of Statistics in Business Decisions Forum
      Students must
      View
      Start discussions: 1
      Post replies: 1
      Make forum posts: 1

      “Some phenomenon cannot be quantitatively measured, honesty of resourcefulness, integrity, goodwill, all important in industry as well as in life generally, are not susceptible of direct statistical measurement"-do you agree or disagree with this statement? Explain the reasons behind your opinion. 

  • Topic-2

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    • Data, Levels of measurement in data, Frequency distribution, Relative frequency, Bar & Pie charts and Frequency Table

      Lecture Objective:

      (a) Understand data and its types

      (b)Understand the levels of measurement in data

      (c) Understand Frequency Table

      (d) Understand relative class frequency

      (e) Understand the Bar chart and Pie chart

      (f) Present data in Bar chart and Pie chart

      (g) Formulate frequency table

      Lecture Contents:

      (a) Primary and Secondary data

      (b) Nominal level data

      (c) Ordinal level data

      (d) Interval level data

      (e) Ratio level data

      (f) Class interval

      (g) Class frequency

      (h) Class midpoint

      (i) Draw Bar chart

      (j) Draw pie chart

    • resource icon
      Types of Data File

      Students can get ideas about various types of data used in real world.

    • forum icon
      Learning from the Lectures Forum
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      Post replies: 1
      Make forum posts: 1

      (a) Define what 'statistics' is.

      (b) Mention at least 3 examples of variables from the real world

      (c) Mention at least 5 things you have learned from the lectures so far


    • resource icon
      Frequency Table, Frequency Distribution & Graphical presentation File
      Students must
      Mark as done
    • Students must
      Mark as done

      Scales of Measurement- Nominal, Ordinal, Interval and Ratio

  • Topic-3

    Concept of Frequency Distribution Table: An Overview | Total Assignment Help

    • Relative & Cumulative Frequency Distribution, Graphical Presentation, and  Frequency Polygon


      Lecture Objectives:

      (a) Understand Relative and Cumulative frequency

      (b) Construct relative and cumulative frequency distribution 

      (c) construct Histogram

      (d) Construct frequency polygon

      Lecture Content:

      (a) Relative frequency distribution

      (b) Cumulative frequency distribution

      (c) Histogram

      (d) Frequency polygon 

    • forum icon
      Facts Checking Forum
      Students must
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      Post replies: 1
      Make forum posts: 1

      (a) What is Frequency table?

      (b) Why should we use Bar chart and Pie chart?

      (c) Mention at least 5 things you have learned from the chapter 

    • hvp icon
      Frequency Table Interactive Content
      Students must
      Mark as done
      To have better understanding on frequency table
    • url icon
      Pie Chart: Definiton, Example and making one in excel URL
      Students must
      Mark as done
    • url icon
      Bar chart: Definition, Examples and making one in Excel URL
      Students must
      Mark as done
    • resource icon
      Frequency, Relative and Cumulative frequency File
      Students must
      Mark as done

  • QUIZ 1 !!!

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  • Topic-4

    Mean, Median, and Mode - Learn How to Find in a Jiffy! - YouTube

    • Identify sample mean, population mean, arithmetic mean & weighted mean, Determine Mode and Median under ungrouped data

      Lecture Objectives:

      • Understand what ‘population mean’ is.
      • Understand what ‘sample mean’ is.
      • Understand arithmetic mean
      • Understand weighted mean
      • Understand what “median” is
      • Understand what “ungrouped data” is.
      • Understand what “mode” is.

       Lecture Contents:

      • population mean
      • sample mean
      • Ungrouped data
      • Median
      • Mode

    • url icon
      What is Mean? Median? Mode? URL
      Students must
      Mark as done
    • url icon
      Don't Memorize! URL
      Students must
      Mark as done
    • url icon
      Mean, median, mode for ungrouped data URL
      Students must
      Mark as done
    • resource icon
      Mean, Median and Mode File
      Students must
      Mark as done
    • lesson icon
      Mean? 💭 Lesson
      Students must
      Mark as done

      Mean, Median and Mode

    • lesson icon
      Median? 💭 Lesson
      Students must
      Mark as done

      Median in Statistics (Formula, Calculation & Examples)

    • lesson icon
      Mode? 💭 Lesson
      Students must
      Mark as done

      How to calculate Mean, Mode, Median, Midrange, and RangeMode Definition, Examples & Purpose | What is Mode? - Video & Lesson Transcript | Study.com

    • forum icon
      Mean, Median, Mode- which one you prefer? Forum
      Students must
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      Start discussions: 1
      Post replies: 1
      Make forum posts: 1

      Among all the measures of location, which one represents location of data more accurately?

  • Topic-5

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  • Quiz 2!!! 💭

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  • Topic 6

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  • Glossary: Topic 1 to Topic 6 ✌️✅

    • glossary icon
      Midterm Glossary
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      Idea Clip Art Cartoon Illustration Stock Vector - Illustration of drawing, concept: 32871201


      • Statistics The science of collecting, organizing, analyzing, and interpreting numerical data for the purpose of making more effective decisions
      • Descriptive statistics, the techniques used to describe the important characteristics of a set of data. This includes organizing the data values into a frequency distribution, computing measures of location, and computing measures of dispersion and skewness. 
      • Inferential statistics, also called statistical inference This facet of statistics deals with estimating a population parameter based on a sample statistic. For example, if a sample of 10 TI-36X solar calculators revealed 2 to be defective, we might infer that 20 percent of the production is defective.
      • Nominal measurement The “lowest” level of measurement. If data are classified into categories and the order of those categories is not important, it is the nominal level of measurement. Examples are gender (male, female) and political affiliation (Republican, Democrat, Independent, all others). If it makes no difference whether male or female is listed first, the data are nominal level. 
      • Ordinal measurement Data that can be ranked are referred to as ordinal measures. For example, consumer response to the sound of a new speaker might be excellent, very good, fair, or poor. Population The collection, or set, of all individuals, objects, or measurements whose properties are being studied
      • Ratio measurement If the distance between numbers is a constant size, there is a true zero point, and the ratio of two values is meaningful, then the data are ratio scale. For example, the distance between $200 and $300 is $100, and in the case of money there is a true zero point. If you have zero dollars, there is an absence of money (you have none). Also the ratio between $200 and $300 is meaningful. 
      • Sample A portion, or subset, of the population being studied. 
      • Charts Special graphical formats used to portray a frequency distribution, including histograms, frequency polygons, and cumulative frequency polygons. Other graphical devices used to portray data are bar charts and pie charts. 
      •  Class The interval in which the data are tallied. For example, $4 up to $7 is a class; $7 up to $11 is another class. 
      • Class frequency The number of observations in each class. If there are 16 observations in the $4 up to $6 class, 16 is the class frequency. Exhaustive Each observation must fall into one of the categories. 
      • Frequency distribution A grouping of data into classes showing the number of observations in each of the mutually exclusive classes. 
      • Midpoint The value that divides the class into two equal parts. For the classes $10 up to $20 and $20 up to $30, the midpoints are $15 and $25, respectively.
      • Histogram A graphical display of a frequency or relative frequency distribution. The horizontal axis shows the classes. The vertical height of adjacent bars shows the frequency or relative frequency of each class. 
      • Relative frequency distribution A frequency distribution that shows the fraction or proportion of the total observations in each class
      • Arithmetic mean The sum of the values divided by the number of values. The symbol for the mean of a sample is and the symbol for a population mean is. 
      • Geometric mean The nth root of the product of all the values. It is especially useful for averaging rates of change and index numbers. It minimizes the importance of extreme values. A second use of the geometric mean is to find the mean annual percent change over a period of time. For example, if gross sales were $245 million in 1990 and $692 million in 2010, the average annual rate of return is 5.33 percent. 
      • Mean deviation The mean of the deviations from the mean, disregarding signs. It is identified as MD. Measure of dispersion A value that shows the spread of a data set. The range, variance, and standard deviation are measures of dispersion.
      • Measure of location A single value that is typical of the data. It pinpoints the center of a distribution. The arithmetic mean, weighted mean, median, mode, and geometric mean are measures of location. 
      • Median The value of the middle observation after all the observations have been arranged from low to high. For example, if observations 6, 9, 4 are rearranged to read 4, 6, 9, the median is 6, the middle value. 
      • Mode The value that appears most frequently in a set of data. For grouped data, it is the midpoint of the class containing the largest number of values. Range It is a measure of dispersion. 
      • The range is found by subtracting the minimum value from the maximum value. 
      • Standard deviation The square root of the variance. 
      • Variance A measure of dispersion based on the average squared differences from the arithmetic mean.
      • Dot plot A dot plot summarizes the distribution of one variable by stacking dots at points on a number line that shows the values of the variable. A dot plot shows all values.
      • Stem-and-leaf display A method to display a variable’s distribution using every value. Values are classified by the data’s leading digit. For example, if a data set contains values between 13 and 84, eight classes based on the 10s digit would be used for the stems. The 1s digits would be the leaves.
    • resource icon
      Class Recording File
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      Mark as done

  • Mid Term Examination (Syllabus, Instruction, Assessment)

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    • Syllabus: 

      Topic 1,2,3,4,5,6

      Instructions:

      • Students have to answer all the questions
      • Total Marks is 25 
      • Time: 1 hour 30 minutes

      Assessment:

      • Student can get full marks if answer has been given with proper calculations, reasonings and interpretations

  • Assignment ✅

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    Assignment Topic: Find the heights of each student of STA-201. (in feet/in cm/in m)

    1. Organize your data set
    2. Mean, Median, Mode
    3. Mean Deviation, Population Variance, Standard Deviation, Range
    4. Interpret your results
    5. Use illustrations where necessary

    • Cover Page: Topic name, Submitted To (Teacher's Information), Submitted By (Student's Information), Course Title, Course Code, Semester Name. 
    • Page Limit: 8 pages 
    • Font type & Size: Calibri, 12, Handwritten is also allowed
    • File type: Pdf  
    • Show creativity 
    • Individual Assignment 
    • Last Date of Submission: November 26, Sunday (Till 11.59 pm)

    • assign icon
      Assignment Portal ✅
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      Make a submission
      Receive a grade

  • Topic 7

    Skewness Stock Illustrations – 90 Skewness Stock Illustrations, Vectors & Clipart - Dreamstime

    • Measures of skewness 

      Lecture objectives:
      • Define what ‘skewness’ is. 
      • Understand to compute the coefficient of skewness under ungrouped data.
      • Describing Relationship between Two Variables
      Lecture Contents:
      • skewness
      • skewed to the right
      • skewed to the left
      • Relationship between Two Variables

       
    • forum icon
      Learning from the chapter 💭 Forum
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      Post replies: 1

      (a) Define what 'Skewness' is.

      (b) Mention at least 3 things you have learned from the chapter.


    • resource icon
      Measures of Skewness File
      Students must
      Mark as done
    • url icon
      What is Skewness? URL
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      View
    • url icon
      Types of Skewness URL
      Students must
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    • url icon
      Skewness URL
      Students must
      View
    • lesson icon
      Skewness Lesson
      Students must
      Mark as done

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    • lesson icon
      💭✅ Lesson
      Students must
      Mark as done

      Skewness Tail Risk Rate Of Return Kurtosis, PNG, 1024x365px, Watercolor, Cartoon, Flower, Frame, Heart Download Free

    • quiz icon
      Short Quiz
      Students must
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      Make attempts: 1

  • Topic 8

    Are Skewness and Kurtosis Useful Statistics? Note: This article was originally published in April 2008 and was updated in Februa

  • Quiz 3! ✅

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  • Topic 9

    90 Correlation Chart Illustrations Illustrations & Clip Art - iStock

  • Topic 10

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  • Topic 11

    Data, graph, index, information, point, statistics, stats icon - Download on Iconfinder

    • Students must
      Mark as done

      Index Number

      Lecture objectives:

      • Define what ‘Index Number’ is.
      • Understand to compute and interpret different types of index

       Lecture Contents:


    • resource icon
      Index File
      Students must
      Mark as done
    • url icon
      Index numbers introduction URL
      Students must
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    • forum icon
      Let's reflect! 💭✅ Forum
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      Post replies: 1

      What's your learning from this topic?

    • resource icon
      Lecture Video File
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  • Presentation ✅

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    Presentation Topic: Find out the Price Index (1 unit) for the following products in Bangladesh from the year 2020-2023:

    1. Rice (any kind)

    2. Edible Oil  (any kind)

    3. Egg (firm, 1 dozen)

    4. Sugar (white)


    Tentative Date: 25th November, 2023 (Saturday)

    • Presentation will be held online
    • Individual Presentation
    • Presentation time for each individual is 2-3 minutes.
    • You should prepare power point slides.

  • Final Exam! ✅

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    • Final Examination: syllabus

      Final Examination: instructions

      • Students have to answer all the questions
      • Total Marks is 40 
      • Time: 2 hours.

      Final Examination: assessment

      • Student can get full marks if answer has been given with proper calculations