Bài giảng nguyên lý thông kê chương 1 introduction to statistics lecturer

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Bài giảng nguyên lý thông kê chương 1 introduction to statistics lecturer

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Lecturer: DAO MINH ANH Faculty of Business and Administration Foreign Trade University Email: anhdm@ftu.edu.vn   - - Textbook Business Mathematics and Statistics – 5th edition (A Francis) References: Essentials of Statistics for Business and Economics – 3rd edition, 2003 (Anderson Sweeney Williams) Statistics for Business and Economics – 4th edition (Paul Newbold)    Class attendance: 10% Group Assignment and presentation: 30% Final exam: 60%   Tracking information: sales, inventory, products being transported, refunded items, customer information (demographic), business performance of suppliers, etc Collecting and analyzing data “Market basket”  Decision making on: - Future trend - Inventory Management - Customer Relationship Management I What is statistics? II Definitions III Descriptive statistics and Inferential statistics IV Qualitative and Quantitative data V Scales of Measurement - What first appear in your mind when we talk about “statistics”? interest rates, population, stock market prices, unemployment… - In a very general way: Statistics numerical information - Furthermore: Statistics Statistical methods - Collect - describe - summarize - present - analyze       Making sense of numerical information Dealing with uncertainty Sampling Analyzing relationships Forecasting Decision making in an uncertain environment  In order to make the right decision or forecast, decision-makers require as much information as possible  However, after being collected numerical information is under the raw form impossible to comprehend thoroughly These information need to be summarized, organized and analyzed so that important features emerges Example: there is a survey on FTU’s students Describe them as quantitative or qualitative, and the scales of measurement Full name: Sex: Male Female Age : Which year student: 1st 2nd 3rd 4th a/ Have you got a part-time job? Yes No b/ If yes, how many hours per week? c/ What you think how much does your part-time job fit your study field? Very suitable Not at all  Define the issue ◦ what are the purpose and objectives of the survey?  Define the population of interest  Formulate survey questions ◦ make questions clear and unambiguous ◦ use universally-accepted definitions ◦ limit the number of questions  Pre-test the survey ◦ pilot test with a small group of participants ◦ assess clarity and length  Determine the sample size and sampling method  Select Sample and administer the survey  Closed-end Questions ◦ Select from a short list of defined choices Example: Major: business liberal arts science other  Open-end Questions ◦ Respondents are free to respond with any value, words, or statement Example: What did you like best about this course?  Demographic Questions ◦ Questions about the respondents’ personal characteristics Example: Gender: Female Male  A Population is the set of all items or individuals of interest Examples: All likely voters in the next election All parts produced today All sales receipts for November ◦  A Sample is a subset of the population ◦ Examples: 1000 voters selected at random for interview A few parts selected for destructive testing Every 100th receipt selected for audit  Less time consuming than a census  Less costly to administer than a census  It is possible to obtain statistical results of a sufficiently high precision based on samples  Items of the sample are chosen based on known or calculable probabilities Probability Samples Simple Random Stratified Systematic Cluster    Every individual or item from the population has an equal chance of being selected Selection may be with replacement or without replacement Samples can be obtained from a table of random numbers or computer random number generators  Population divided into subgroups (called strata) according to some common characteristic  Simple random sample selected from each subgroup  Samples from subgroups are combined into Population Divided into strata one Sample  Decide on sample size: n  Divide frame of N individuals into groups of k individuals: k=N/n  Randomly select one individual from the 1st group  th Select every k N = 64 individual thereafter n=8 k=8 First Group   Population is divided into several “clusters,” each representative of the population A simple random sample of clusters is selected ◦ All items in the selected clusters can be used, or items can be chosen from a cluster using another probability sampling technique Population divided into 16 clusters Randomly selected clusters for sample  There are three kinds of lies… ◦ Lies ◦ Damn Lies ◦ Statistics  You need to make statistics work for you, not lie for you! THANK YOU! Describe the variable implicit in these 10 items as quantitative or qualitative, and describe the scale of measurement Age of household head Sex of household head Number Use of people in household of electric heating (yes/no) Numbers of large appliances used daily Average number of hours heating is on Average number of heating days Household incomes Average monthly electric bill 10.Ranking of this electric company among electricity suppliers  You have to a survey on vacation/ summer holiday of FTU’s students Work with your groups to create a questionnaire for this assignment  It should contain: - The goal of the survey - Objects - Content [...]...   Statistics is the science of uncertainty” In statistics we have to deal with the question what might be, what could be… not what is One task of statistics is to estimate the level of uncertainty  E.g: Before bringing a new product to market, market research survey about the likely level of demand of this product maybe... point-of-sale scanners at retail checkout counters are used to collect data for a variety of marketing research applications Production A variety of statistical quality control charts are used to monitor the output of a production process  Finance Financial advisors use price-earnings ratios and dividend yields to guide their investment recommendations 1/ Variable is a characteristic that changes or varies... Sample is an observed subset of population values Population vs Sample Population a b Sample cd b ef gh i jk l m n o p q rs t u v w x y z c gi o n r y u Statistics Descriptive Statistics Inferential Statistics    Descriptive statistics: Methods used to summarize and describe the main features of the whole population in quantitative term Tabular, graphical, and numerical methods (mean, median, variance,...   Labels or names used to identify an attribute of each element Often be referred to as categorical data Nominal or ordinal scale of measurement will be applied to summarize this kind of data Usually nonnumeric data Therefore, appropriate statistical analyses are rather limited in comparison with those of quantitative data  Eye colors: 1. Brown 2.Black  Marital status: 1 Single 2 Married 3 Divorced... - Characterize data e.g., Calculate mean = ∑x n i    Inferential statistics: Procedures used to draw conclusions or inferences about the characteristics of a population from information obtained from the sample Making estimates, testing hypothesis… Used when we can not enumerate the whole population Population parameters Sample statistics (known) Inference Sample (unknown, but can be estimated from... (nominal scale) to the most sophisticated one (interval/ratio scale) Level of measurements Measurements Rankings Ordered Categories Categorical Codes ID Numbers Category Names Ratio/Interval Scale Ordinal Scale Nominal Scale Highest Level Complete Analysis Higher Level Mid-level Analysis Lowest Level Basic Analysis  Nominal Data Data are are labels labels or or names names used used to to identify identify... concerning a population based on sample results  Estimation ◦ e.g., Estimate the population mean weight using the sample mean weight  Hypothesis Testing ◦ e.g., Use sample evidence to test the claim that the population mean weight is 12 0 pounds Data Data can can be be classified classified as as being being qualitative qualitative or or quantitative quantitative Depends Depends on on whether whether the the... Humanities, Humanities, Education, Education, and and so so on on Alternatively, Alternatively, aa numeric numeric code code could could be be used used for for the the school school variable variable (e.g (e.g 11 denotes denotes Business,2 Business,2 denotes denotes Humanities, Humanities, 33 denotes denotes Education, Education, and and so so on) on) ... these variables     Reliable predictions play a key role in management and making decision For example: investment decisions must be made well ahead of the time at which a new product can be brought to market; Essentially, forecasts of future values are obtained through the information of past behaviors The analysis of this information suggests future trend  A particular problem for management: making... a new product to market, market research survey about the likely level of demand of this product maybe should the survey cover all potential buyers undertaken? (population)? Absolutely impossible due to the huge costs of time, money, people… Sampling Let’s consider some examples below: (i) Does the growth rate of money supply influence the inflation rate? (ii) If the price of a product rise by 5%,

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Mục lục

  • STATISTICS FOR BUSINESS AND ECONOMICS

  • Slide 2

  • Grade Scale

  • “Giant” Wal-mart

  • 35 terabytes of data

  • Chapter 1 Introduction to Statistics for Business and Economics

  • I. What is statistics?

  • Slide 8

  • More details, Statistics covers some major jobs:

  • Making sense of numerical information

  • Dealing with uncertainty

  • Sampling

  • Analyzing relationships

  • Forecasting

  • Decision making in an uncertain environment

  • Applications in Business and Economics

  • Applications in Business and Economics

  • Applications in Business and Economics

  • II/ Definitions

  • Slide 20

  • III/ Descriptive statistics and Inferential statistics

  • 1/ Descriptive statistics

  • Descriptive Statistics

  • 2/ Inferential Statistics

  • Inferential Statistics

  • Slide 26

  • IV. Quantitative and qualitative data

  • Qualitative Data

  • Examples

  • Quantitative Data

  • Slide 31

  • V. Scales of Measurement

  • Slide 33

  • Slide 34

  • Scales of Measurement

  • Example

  • Slide 37

  • Slide 38

  • Slide 39

  • Slide 40

  • Slide 41

  • Slide 42

  • Slide 43

  • Slide 44

  • Slide 45

  • Slide 46

  • Slide 47

  • Survey Design Steps

  • Slide 49

  • Types of Questions

  • Populations and Samples

  • Why Sample?

  • Statistical Sampling

  • Simple Random Samples

  • Stratified Samples

  • Systematic Samples

  • Cluster Samples

  • Learn to View Statistics with a Critical Eye

  • End of chapter 1

  • Exercise 1

  • Exercise 2

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