1. Understand the Types of Quantitativedatawhichcan Be Usedbyorganisationsto Monitor And

Alfred Nobel Open Business School Switzerland

QuantitativeMethods

This unit willenablelearnerstofurtherdevelopunderstanding and skillsin the application of quantitativemethodsappropriatetosupportdecision-takinginorganisations.

IndicativeContent

1. Understand the types of quantitativedatawhichcan be usedbyorganisationsto monitor and improvetheir performance

- The nature of data and types of datasuchasqualitative and quantitative, and of information, howdatacan be turnedintoinformation and informationusedtoinformdecisionmaking.

- Interpretingdatafrom a variety of sourcesusingdifferentmethods of analysiswithadvantages, disadvantages and limitations of each

- Use and comparison of samplingtechniquesincluding random samplingwith and withoutreplacement; stratifiedsampling; clustersampling; systematicsampling and othertypes of samplingtechniques

2. Be abletoanalyse and evaluateraw business datatoinformdecisiontaking

- Quantitativemethodsthatareusedtoanalyse and evaluatedata

- Descriptivestatistics:

o Measures of centraltendency (e.g. mean, median)

o Measures of variability (e.g. range, standard deviation)

o Applicationto business data (e.g. findingaverageearnings, measuring)

o Variabilityin business processessuchasqueuingtimes and customerarrivalrates

-Inferentialstatistics, the differencebetweensample and population and reliability of estimatesfromsamples

-Measuringassociation:

o Use of scatterplots, correlation and regressionanalysis (linear), simpleforecasting

o Business applicationssuchas the associationbetween output and cost, advertising and sales

o Evaluatinguse of software suchas Excel and SPSS toperformrawdataanalysis

3. Be abletoapply a range of quantitativemethodstosupporteffective business decisiontaking

- Probabilitydistributions and applicationto business decisions, Normaldistribution (e.g. weights and measuresregulations and statisticalprocesscontrol), Poisson distribution (e.g. customerarrivalrates) and binomialdistribution (e.g. inspectionsampling), Inference (e.g. margins of error and confidencelimits)

- Inventory management including optimum inventory and economicorderquantities

capacity management and factorseffectingcapacity and maximum output rates, forecastcapacity and the use of decisiontrees

-The issue of variabilityin business processes (e.g. arrivalrates of customers and timetakentodealwithcustomers), and howthisleadsto a trade-offbetweenwaitingtime and processutilisation

-Quantitativemethodsusedtoanalysetrends over timesuchastime series analysis and index numbers and howtheysupportplanning and decisionmaking

4. Be abletoreportondata and communicatefindingstosupportdecisiontaking

- Identifyingdata: numerical, bothdiscrete and continuous; Categoricaldata-nominalorordinal

- Levels of measurement - nominal, ordinal, interval, ratio

•Centre, and spread of data, ordering, frequency and scatter plots, ranking.

•Levels of measurement - nominal, ordinal, interval, ratio

•Time series analysis, indices, histograms, charts, tables, bar and line graphs and theiruseinrepresenting and interpretingdata

•Choosing the most effectivewaysanalysingdata and of communicating the results of the analysis and informationfordecisiontakingusingtables and chartswithappropriatelimitationsconclusions and recommendationsgiven

•Utilising Software forproducingcharts/tables

Buchhaltung: Löwenstrasse 20, CH-8001 Zürich, Büro: Bahnhofstrasse 28, 2. OG, CH-8307 Illnau-Effretikon, Tel: +41-445588344, E-mail: , Web: , Firmennummer: CHE-106.753.110