AQA - Business Statistics , Quantitative Analysis Peter Matthews matthewsp@bpc.ac.uk

1. AQA - Business Statistics , Quantitative AnalysisPeter Matthewsmatthewsp@bpc.ac.uk FDA B&M 2011-12

2. The aim today is to describe What Are Statistics Where are they used LECTURE

3. What is Statistics I need help! • Applications in Business • and Economics • Statistics is the science of learning from data, and of measuring, controlling, and communicating uncertainty • Plus : - it’s a pain and lots of people hate it.

4. Application Areas of Statistics Accounting • Auditing • Costing Finance • Financial trends • Forecasting Management • Describe employees • Quality improvement Marketing • Consumer preferences • Marketing mix effects

5. Applications in Business and Economics • 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 aspect of it.

6. Applications in Business and Economics • 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.

7. Applications in Business and Economics • Finance Financial advisers use price-earnings ratios and dividend yields to guide their investment recommendations.

8. Why Collect Data? • Obtain input to a research study • Measure performance • Assist in formulating decision alternatives • Satisfy curiosity • Knowledge for the sake of knowledge

9. Data and Data Sets • TheData are the facts and figures collected, summarized, analyzed, and interpreted. • Data collected in a particular study are referred to as the data set.

10. Elements, Variables, and Observations • The elements are the entities on which data are collected. • A variable is a characteristic of interest for • the elements. • The set of measurements collected for a particular element is called an observation. • The total number of data values in a data set is the number of elements multiplied by the number of variables.

11. Data, Data Sets, Elements, Variables, and Observations Variables Observation Element Names Stock Annual Earn/ Exchange Sales(£M) Share(£) Company AMEX 73.10 0.86 OTC 74.00 1.67 NYSE 365.70 0.86 NYSE 111.40 0.33 AMEX 17.60 0.13 Dataram EnergySouth Keystone LandCare Psychemedics Data Set

12. Qualitative and Quantitative Data Data can be further classified as being qualitative or quantitative. The statistical analysis that is appropriate depends on whether the data for the variable are qualitative or quantitative. In general, there are more alternatives for statistical analysis when the data are quantitative.

13. Qualitative Data Labels or names used to identify an attribute of each element Often referred to as categorical data Use either the nominal or ordinal scale of measurement Can be either numeric or nonnumeric Appropriate statistical analyses are rather limited

14. Quantitative Data Quantitative data indicate how many or how much: discrete, if measuring how many (finite) continuous, if measuring how much (infinite) Quantitative data are always numeric. Ordinary arithmetic operations are meaningful for quantitative data.

15. Types of Data

16. Data Sources

17. Data Sources • Existing Sources (Secondary) Within a firm – almost any department Business database services – Dow Jones & Co. Government agencies - U.S. Department of Labor Industry associations – Travel Industry Association of America Special-interest organizations – Graduate Management Admission Council Internet – more and more firms

18. Data Sources (Continued) • Statistical Studies In experimental studies the variables of interest are first identified. Then one or more factors are controlled so that data can be obtained about how the factors influence the variables. In observational (non-experimental) studies no attempt is made to control or influence the variables of interest. a survey is a good example

19. Data Acquisition Considerations Time Requirement • Searching for information can be time consuming. • Information may no longer be useful by the time it is available. Cost of Acquisition • Organizations often charge for information even when it is not their primary business activity. Data Errors • Using any data that happens to be available or that were acquired with little care can lead to poor and misleading information.

20. What Is Statistics? • Collecting data • e.g., Survey • Presenting data • e.g., Charts & tables • Characterizing data • e.g., Average Why? Data Analysis Decision-Making

21. Descriptive Statistics • Descriptive statistics are the tabular, graphical, and numerical methods used to summarize data. Descriptive Statistics: These are statistical methods used to describe data that have been collected.

22. Example:Dixon Car Repair The manager would like to have a better understanding of the cost of parts used in the engine tune-ups performed in the shop. She examines 50 customer invoices for tune-ups. The costs of parts, rounded to the nearest £, are listed on the next slide.

23. Example: Hudson Auto Repair • Sample of Parts Cost for 50 Tune-ups

24. Tabular Summary: Frequency and Percent Frequency Parts Cost (£) Percent Frequency Parts Frequency 2 13 16 7 7 5 50 4 26 32 14 14 10 100 50-59 60-69 70-79 80-89 90-99 100-109 (2/50)100

25. 18 16 14 12 10 8 6 4 2 Graphical Summary: Histogram Tune-up Parts Cost Frequency Parts Cost ($) 5059 6069 7079 8089 9099 100-110

26. Inferential Statistics • Involves • Estimation • Hypothesis testing • Purpose • Make decisions about population characteristics Population? Inferential Statistics: These are statistical methods used to find out something about population based on a sample.

27. Statistical Inference Population  the set of all elements of interest in a particular study Sample  a subset of the population Statistical inference  the process of using data obtained from a sample to make estimates and test hypotheses about the characteristics of a population Census  collecting data for a population Sample survey  collecting data for a sample

28. Statistical Analysis Using Microsoft Excel • Statistical analysis typically involves working with large amounts of dataa. • Computer software is typically used to conduct the analysis. • Frequently the data that is to be analyzed resides in a spreadsheet. • Modern spreadsheet packages are capable of data management, analysis, and presentation. • MS Excel is the most widely available spreadsheet software in business organizations.

29. Statistical Analysis Using Microsoft Excel • Excel Worksheet (showing data) Note: Rows 10-51 are not shown.

30. Statistical Analysis Using Microsoft Excel • Excel Formula Worksheet Note: Columns A-B and rows 10-51 are not shown.

31. Statistical Analysis Using Microsoft Excel • Excel Value Worksheet Note: Columns A-B and rows 10-51 are not shown.