Lecturer: DAO MINH ANH Faculty of Business and Administration Foreign Trade University

 Textbook Business Mathematics and Statistics – 5 th edition (A. Francis)  References: - Essentials of Statistics for Business and Economics – 3 rd edition, 2003 (Anderson Sweeney Williams) - Statistics for Business and Economics – 4 th 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

 “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 undertaken? should the survey cover all potential buyers (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%, what is the effect on the sales of this product? - The relationships between variables will be analyzed in a quantitative way not qualitative way based on the past behaviors of 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 decisions in the condition of incomplete information  Therefore, under such circumstances, possible options should be raised and considered

Accounting Public accounting firms use statistical sampling procedures when conducting audits for their clients. Economics Economists use statistical information in making forecasts about the future of the economy or some aspects of it.

Marketing Electronic 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 over time for different individuals or objects under consideration 2/ Experimental Units (elements) are items or objects on which measurements are taken 4/ Population is the WHOLE set of all items or individuals of interest 5/ Sample is an observed subset of population values

Population vs. Sample a b c d ef gh i jk l m n o p q rs t u v w x y z PopulationSample b c g i n o r u y

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, standard deviation…)  Used when we can enumerate the whole population

- Collect data e.g., Survey, Observation, Experiments - Present data e.g., Charts and graphs - Characterize data e.g., Calculate mean =

 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

Sample statistics (known) Population parameters (unknown, but can be estimated from sample evidence Inference

 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 120 pounds Drawing conclusions and/or making decisions concerning a population based on sample results.

Data can be classified as being qualitative Data can be classified as being qualitative or quantitative. or quantitative. Data can be classified as being qualitative Data can be classified as being qualitative or quantitative. or quantitative. Depends on whether the data are qualitative or quantitative, we choose the most appropriate statistical methods Depends on whether the data are qualitative or quantitative, we choose the most appropriate statistical methods In general, there are more statistical analysis for In general, there are more statistical analysis for quantitative data. In general, there are more statistical analysis for In general, there are more statistical analysis for quantitative data.

 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 3.Blue 4.Green  Marital status: 1. Single 2. Married 3. Divorced 4. Widowed

 Quantitative data can be described as data under the numeric form. It indicates how many or how much: There are two types of quantitative data: discrete data: - can measure precisely. - Only a finite number of values is possible. - Example: Continuous data: - can not measured precisely - An infinite number of values is possible. - Example:

E.g. (i)The number of students in a class (ii)The number of correct answers in a test (iii)People’s height, weight; students’ GPA

 Scales of measurement include: NominalInterval OrdinalRatio The scale determines the amount of information The scale determines the amount of information contained in the data. contained in the data. The scale determines the amount of information The scale determines the amount of information contained in the data. contained in the data. The scale indicates the data summarization and The scale indicates the data summarization and statistical analyses that are most appropriate. statistical analyses that are most appropriate. The scale indicates the data summarization and The scale indicates the data summarization and statistical analyses that are most appropriate. statistical analyses that are most appropriate.

 These scales of measurement gradually develop, from the simplest form (nominal scale) to the most sophisticated one (interval/ratio scale).

Ratio/Interval Scale Ordinal Scale Nominal Scale Highest Level Complete Analysis Higher Level Mid-level Analysis Lowest Level Basic Analysis Categorical Codes ID Numbers Category Names Rankings Ordered Categories Measurements Level of measurements

 Nominal Data are labels or names used to identify an Data are labels or names used to identify an attribute of the element. attribute of the element. Data are labels or names used to identify an Data are labels or names used to identify an attribute of the element. attribute of the element. A nonnumeric label or numeric code may be used. A nonnumeric label or numeric code may be used.

Students of a university are classified by the school in which they are enrolled using a nonnumeric label such as Business, Humanities, Education, and so on. Alternatively, a numeric code could be used for the school variable (e.g. 1 denotes Business,2 denotes Humanities, 3 denotes Education, and so on). Students of a university are classified by the school in which they are enrolled using a nonnumeric label such as Business, Humanities, Education, and so on. Alternatively, a numeric code could be used for the school variable (e.g. 1 denotes Business,2 denotes Humanities, 3 denotes Education, and so on).

Please state which fuel are you using at home? 1. Firewood 2. Coal 3. Oil 4. Gas Please state which fuel are you using at home? 1. Firewood 2. Coal 3. Oil 4. Gas

 Ordinal The data have the properties of nominal data and The data have the properties of nominal data and the order or rank of the data is meaningful. the order or rank of the data is meaningful. The data have the properties of nominal data and The data have the properties of nominal data and the order or rank of the data is meaningful. the order or rank of the data is meaningful. A nonnumeric label or numeric code may be used. A nonnumeric label or numeric code may be used.

Students of a university are classified by their class standing using a nonnumeric label such as Freshman, Sophomore, Junior, or Senior. Alternatively, a numeric code could be used for the class standing variable (e.g. 1 denotes Freshman, 2 denotes Sophomore, and so on). Students of a university are classified by their class standing using a nonnumeric label such as Freshman, Sophomore, Junior, or Senior. Alternatively, a numeric code could be used for the class standing variable (e.g. 1 denotes Freshman, 2 denotes Sophomore, and so on).

Please order the kind of fuel that is the most favorite one for you? ( ) Firewood () Coal () Oil () Gas Please order the kind of fuel that is the most favorite one for you? ( ) Firewood () Coal () Oil () Gas

 Interval The data have the properties of ordinal data, and The data have the properties of ordinal data, and the interval between observations is expressed in the interval between observations is expressed in terms of a fixed unit of measure. terms of a fixed unit of measure. The data have the properties of ordinal data, and The data have the properties of ordinal data, and the interval between observations is expressed in the interval between observations is expressed in terms of a fixed unit of measure. terms of a fixed unit of measure. Interval data are always numeric. Interval data are always numeric. There is no zero value that indicates There is no zero value that indicates that nothing exists for the variable at the zero point. that nothing exists for the variable at the zero point. There is no zero value that indicates There is no zero value that indicates that nothing exists for the variable at the zero point. that nothing exists for the variable at the zero point.

 Interval The ratio of two values of interval scale is not The ratio of two values of interval scale is not Meaningful because there is no zero value in this scale. The ratio of two values of interval scale is not The ratio of two values of interval scale is not Meaningful because there is no zero value in this scale. Example: Melissa has an SAT score of 800, while Kevin has an SAT score of 400. Melissa scored 400 points more than Kevin.

Please state your opinion on customer service at one restaurant? Not friendlyFriendly Please state your opinion on customer service at one restaurant? Not friendlyFriendly

 Ratio The data have all the properties of interval data The data have all the properties of interval data and the ratio of two values is meaningful. and the ratio of two values is meaningful. The data have all the properties of interval data The data have all the properties of interval data and the ratio of two values is meaningful. and the ratio of two values is meaningful. Variables such as distance, height, weight, and time Variables such as distance, height, weight, and time use the ratio scale. use the ratio scale. Variables such as distance, height, weight, and time Variables such as distance, height, weight, and time use the ratio scale. use the ratio scale. This scale must contain a zero value that indicates This scale must contain a zero value that indicates that nothing exists for the variable at the zero point. that nothing exists for the variable at the zero point. This scale must contain a zero value that indicates This scale must contain a zero value that indicates that nothing exists for the variable at the zero point. that nothing exists for the variable at the zero point.

Melissa’s college record shows 36 credit hours earned, while Kevin’s record shows 72 credit hours earned. Kevin has twice as many credit hours earned as Melissa.

Assume that you spend VND 100,000 for your family’s fuel. Please distribute this amount for different kinds that you are interested in? 1. Firewood VND 2. Coal VND 3. Oil VND 4. Gas VND Assume that you spend VND 100,000 for your family’s fuel. Please distribute this amount for different kinds that you are interested in? 1. Firewood VND 2. Coal VND 3. Oil VND 4. Gas VND

Example: there is a survey on FTU’s students. Describe them as quantitative or qualitative, and the scales of measurement 1. Full name: Sex: Male Female 3. Age : 4. Which year student: 1 st 2 nd 3 rd 4 th 5. a/ Have you got a part-time job? Yes No b/ If yes, how many hours per week? c/ What do you think how much does your part-time job fit your study field? Very suitableNot 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 100 th 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 SystematicStratifiedCluster

 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 one Population Divided into 4 strata 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 1 st group  Select every k th individual thereafter N = 64 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 1. Age of household head 2. Sex of household head 3. Number of people in household 4. Use of electric heating (yes/no) 5. Numbers of large appliances used daily 6. Average number of hours heating is on 7. Average number of heating days 8. Household incomes 9. Average monthly electric bill 10. Ranking of this electric company among 4 electricity suppliers

 You have to do 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