001 Lesson 1 Statistical Techniques for Business & Economics
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001 Lesson 1 Statistical Techniques for Business & Economics

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For Hanze Year 1 students

For Hanze Year 1 students

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001 Lesson 1 Statistical Techniques for Business & Economics 001 Lesson 1 Statistical Techniques for Business & Economics Presentation Transcript

  • IBS Statistics Year 1 Dr. Ning DING n.ding@pl.hanze.nl I007, Friday & Monday
  • Table of content • Chapter 1: What is statistics? – Why study statistics? – What is meant by statistics? – Types of statistics – Types of variables – Levels of measurement • Norminal-Level Data • Ordinal-Level Data • Interval-Level Data – Ethics and Statistics • Chapter 2: Describing data – Frequency tables – Frequency distributions – Graphic presentation
  • Learning Goals • Chapter 1: What is statistics? – Understand why we study statistics – Explain what is meant by descriptive and inferential statistics – Distinguish between a qualitative and quantitative variable – Describe how a discrete variable is different from a continous variable – Distinguish among the nominal, ordinal, interval and ratio levels of measurement • Chapter 2: Describing data – Organize qualitative data into a frequency table – Present a frequency table as a bar chart or a pie chart – Organize quantitative data into a freqency distribution – Present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.
  • Chapter 1: What is Statistics? 1. Introduction Statistics are everywhere.
  • Chapter 1: What is Statistics? 1. Introduction
  • Chapter 1: What is Statistics? 1. Introduction Statistics help you make decisions.
  • Chapter 1: What is Statistics? 1. Introduction Statistics give you a better understanding.
  • Chapter 1: What is Statistics? 1. Introduction 1. Adequate information? Additional information? 2. No misleading information? 3. Summarize the information. 4. Analyze available information. 5. Conclusions!
  • Chapter 1: What is Statistics? 1. Introduction Statistics: The science of collecting, organizing, presenting, analyzing and interpreting data to assist in making more effective decisions.
  • Chapter 1: What is Statistics? 1. Introduction Making decisions Interpret data Present data Analyze data Organize data Collect data
  • Chapter 1: What is Statistics? 2. Types of Statistics Descriptive Statistics: Methods of organizing, summarizing and presenting data in an informative way. Inferential Statistics: Methods used to estimate a property of a population on the basis of a sample.
  • Chapter 1: What is Statistics? 2. Types of Statistics Descriptive Inferential Statistics: Statistics:
  • Chapter 1: What is Statistics? 2. Types of Statistics Population: The entire set of individual or objects of interest or the measurements obtained from all individuals or objects of interest. Sample: A portion, or part, of the population of interest.
  • Chapter 1: What is Statistics? 2. Types of Statistics Population: Sample: Play
  • Chapter 1: What is Statistics? 3. Types of Variables Qualitative: nonnumeric, attribute Quantitative: numerical
  • Chapter 1: What is Statistics? 3. Types of Variables Quantitative: Qualitative:
  • Chapter 1: What is Statistics? 3. Types of Variables Discrete counting or Continuous measuring
  • Chapter 1: What is Statistics? 4. Levels of Measurement Nominal: •Data categories are represented by labels or names. •Even when the labels are numerically coded, the data categories have no logical order. •Example: •Eye colour, gender, religious affiliation Ordinal: •Data classifications are represented by sets of labels or names (high, medium, low) that have relative values. •Because of the relative values, the data classified can be ranked or ordered. •Example: •During a taste test of 4 soft drinks, Mellow Yellow was ranked number 1, Sprite number 2, Seven-up number 3, and Orange Crush number 4.
  • Chapter 1: What is Statistics? 4. Levels of Measurement Nominal: Ordinal: No logical order Ranked or ordered
  • Chapter 1: What is Statistics? 4. Levels of Measurement Interval: •Similar to the ordinal level, with the additional property that meaningful amounts of differences between data values can be determined. •There is no natural zero point. •Example: •Temperature on the Fahrenheit scale. Ratio: •The interval level with an inherent zero starting point. •Differences and ratios are meaningful for this level of measurement. •Examples: •Monthly income; distance travelled by manufacturer’s representatives per month.
  • Chapter 1: What is Statistics? 4. Levels of Measurement Online Animation Nominal: Ordinal: Interval: Ordered, Equal differences Ratio: Zero
  • vels of Measurement Chapter 1: What is Statistics? 4. Levels of Measurement
  • Chapter 1: What is Statistics? Exercises 1-a For each of the following, determine whether the group is a sample or a population. •The participants in a study of a new cholesterol drug. Sample •The drivers who received a speeding ticket Kansas City last month. Population •Those on welfare in Cook County (Chicago), Illinois. Population •The 30 stocks reported as a part of the Dow Jones Industrial Average. Sample P14. N.4 Ch.1
  • Chapter 1: What is Statistics? Exercises 1-b Refer to the Real Estate data at the back of the text, which report information on homes sold in the Denver, Colorado, area last year. Consider the following variables: selling price, number of bedrooms, township, and distance from the center of the city. •Which of the variables are qualitative and which are quantitative? township all the rest… •Determin the level of measurement for each of the variables. Township = nominal level All the rest…=ratio P18. N.16 Ch.1
  • Chapter 2: Describing data 2.1 Frequency Table Frequency Table: •A grouping of qualitative data into mutually exclusive classes showing the number of observations in each class. Example: Ice cream 20 vendors Choco 6 7 5 7 7 8 7 6 9 7 Vanilla 4 10 6 8 8 9 5 6 4 8
  • Chapter 2: Describing data 2.1 Frequency Table Relative Class Frequencies: •Show the fraction of the total number of observations in each class Example: Ice cream 20 vendors Choco 6 7 5 7 7 8 7 6 9 7 Vanilla 4 10 6 8 8 9 5 6 4 8
  • Chapter 1: What is Statistics? Exercises 2-a A total of 1,000 residents in Minnesota were asked which season they preferred. The results were 100 liked winter best, 300 liked spring, 400 liked summer, and 200 liked fall. If the data were summarized in a frequency table, how many classes would be used? What would be the relative frequencies for each class? P27. N.3 .Ch.2
  • Chapter 2: Describing data 2.2 Graphic Presentation of Qualitative Data Bar Chart: •The classes are reported on the horizontal axis •The class frequencies on the vertical axis •The class frequencies are proportional to the heights of the bars. Example: Ice cream 20 vendors Ice Cream Sales 70 Choco, 69 Vanilla, 68 65 Choco Axis 60 Vanilla 55 50 Choco Vanilla Types
  • Chapter 2: Describing data 2.2 Graphic Presentation of Qualitative Data Pie Chart: •Shows the proportion or percent that each class represents of the total number of frequencies Example: Ice cream 20 vendors 49.64% 50.36% 1 2
  • Chapter 2: Describing data 2. Frequency Distribution Frequency Distribution: •A grouping of data into mutually exclusive classes showing the number of observations in each class.
  • Chapter 2: Describing data 2. Frequency Distribution Frequency Distribution: •A grouping of data into mutually exclusive classes showing the number of observations in each class.
  • Chapter 2: Describing data 2. Frequency Distribution Step 1: Just enough recipe 2 to the k rule N=27 number of class=5 Step 2: Class Interval 10 -< 20 4 20 -< 30 1 (55-14)/5 ≈ 8 30 -< 40 10 Step 3: Choose nice “round” boundaries 40 -< 50 9 Step 4: Try to avoid empty and open classes 50 -< 60 3 N=27 Practice
  • Chapter 2: Describing data Exercises 2-b A set of data consists of 45 observations between $0 and $29. What size would you recommend for the class interval? 25 = 32, 26 = 64, suggests 6 classes i> $30 - $0 =5 6 Use interval of 5 P33. N.8 .Ch.2
  • Chapter 2: Describing data Exercises 2-b The Quick Change Oil Company has a number of outlets in the metropolitan Seattle area. The daily number of oil changes at the Oak Street outlet in the past 20 days are: 65 98 55 62 79 59 51 90 72 56 70 62 66 80 94 79 63 73 71 85 a. How many classes would you recommend? a. 24 = 16, 25 = 32, suggests 5 classes b. What class interval would you suggest? 99 - 51 i> ≈ 9 b. Use interval of 10 5 P34. N.12.Ch.2
  • Chapter 2: Describing data Exercises 2-b The Quick Change Oil Company has a number of outlets in the metropolitan Seattle area. The daily number of oil changes at the Oak Street outlet in the past 20 days are: 65 98 55 62 79 59 51 90 72 56 70 62 66 80 94 79 63 73 71 85 c. What lower limit would you recommend for the first class? c. 50 P34. N.12.Ch.2
  • Chapter 2: Describing data 3. Graphic Presentation Histogram •The classes are marked on the horizontal axis •The class frequencies on the vertical axis •The class frequencies are represented by the heights of the bars and the bars are adjacent to each other. Polygon: •The shape of a distribution •Similar to a histogram
  • Chapter 2: Describing data 3. Graphic Presentation Histogram Example: 16 Amount of € spent on books by 50 students 14 12 No. of students 10 8 6 4 2 0 25 75 125 175 225 275 325 375 425 Amount in €
  • Chapter 2: Describing data 3. Graphic Presentation Polygon Example: Amount of € spent on books by 50 students 16 14 12 No. of students 10 8 6 4 2 0 125 175 225 275 325 375 425 Amount in €
  • Chapter 2: Describing data 3. Graphic Presentation Cumulative frequency distribution: used to determine how many or what proportion of the data values are below or above a certain value. Amount of € spent on books by 50 students 60 50 Cumulative frequency 40 30 20 10 0 100 150 200 250 300 350 400 450 Amount in €
  • Chapter 2: Describing data 3. Graphic Presentation
  • Chapter 1: What is Statistics? Summary • Chapter 1: What is statistics? – Understand why we study statistics – Explain what is meant by descriptive and inferential statistics – Distinguish between a qualitative and quantitative variable – Describe how a discrete variable is different from a continous variable – Distinguish among the nominal, ordinal, interval and ratio levels of measurement • Chapter 2: Describing data – Organize qualitative data into a frequency table – Present a frequency table as a bar chart or a pie chart – Organize quantitative data into a freqency distribution – Present a frequency distribution for quantitative data using histograms, frequency polygons, and cumulative frequency polygons.
  • Chapter 1: What is Statistics? Exercises 1-a What is the level of measurement for each of the following variables? • A. student IQ ratings Interval • B. distance students travel to class Ratio • C. student scores on the first statistics test Interval • D. a classification of students by state of birth Nominal • E. a ranking of students as freshmen, sophomore, junior, and senior Ordinal • F. Number of hours students study per week Ratio
  • Chapter 1: What is Statistics? Exercises 1-b Place these variables in the following classification tables. a. Salary b. Gender Discrete Continuous c. Sales volumen of b. Gender d. Soft drink preference MP3 players Qualitative d. Soft drink preference e. Temperature f. SAT scores f. SAT scores a. Salary g. Student rank g. Student rank in class c. Sales volume of MP3 players in class Quantitative h. Rating of a h. Rating of a finance professor e. Temperature finance professor i. Number of home computers i. Number of home computers P16. N.9 Ch.1
  • Chapter 1: What is Statistics? Exercises 1-c Place these variables in the following classification tables. a. Salary b. Gender Discrete Continuous c. Sales volumen of b. Gender MP3 players Nominal d. Soft drink preference d. Soft drink preference e. Temperature Ordinal f. SAT scores g. Student rank in class h. Rating of a finance professor g. Student rank in class f. SAT scores e. Temperature h. Rating of a Interval finance a. Salary professor i. Number of Ratio c. Sales volume of MP3 players home computers i. Number of home computers
  • Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 1. Compare the total sales in the two months. What do you conclude? Has there been an increase in sales? P17. N.13 Ch.1
  • Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 1. Compare the total sales in the two months. What do you conclude? Has there been an increase in sales? (1,056,144-866,243) Total sales increased 189,901 units or 21.9%. 866,243
  • Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 2. Compare the percent of the Big Three market for each company. Did the market increase or did GM steal sales from the other companies? Cite evidence.
  • Chapter 1: What is Statistics? Exercises 1-d The table below reports the number of cars and light trucks sold by the Big Three automobile manufacturers for June 2004 and June 2005. 2. Compare the percent of the Big Three market for each company. Did the market increase or did GM steal sales from the other companies? Cite evidence. GM increased the market share by 9 percentage points from 43% to 52%. Crysler lost 3% and Ford lost 6%. All three companies increased the nubmer of units sold.