# Ch02 - Admin Recitations Clicker registration – Sec 301...

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Unformatted text preview: Admin Recitations Clicker registration – Sec 301, 1pm, room 340 – Sec 302, 2pm, room 300 – Xiaochuan Qin Chapter 2 Chapter 2 1 Chapter Two Data Collection Chapter 2 Chapter 2 2 Why summarize data? Chapter 2 Chapter 2 3 Why do we need to summarize data? Lists or tables of numbers are difficult for our brain to process Need to organize numbers so that we can make broad observations Observations based on data help us make better decisions about business and our personal lives Chapter 2 Chapter 2 4 Individuals vs. Variables An individual is the thing we count, such as students, cars, countries or invoice statements A variable is some characteristic about the individual. Students - grade point average, year in school Cars - color, price Countries - population, type of climate Invoice statements - number of errors, customer name Chapter 2 Chapter 2 5 Categorical vs. Numerical Variables Categorical data puts Numerical data individuals into assigns numbers groups – – – – year in school color type of climate customer name Chapter 2 Chapter 2 – – – – grade point average price population number of errors 6 Types of Data Categorical (qualitative) Numerical (quantitative) Coded 1=Action 2=Comedy… Binary 0=Male 1=Female Chapter 2 Chapter 2 Discrete (# students) Continuous (Weight) 7 Discrete vs. Continuous DISCRETE 1. 2. 3. 4. CONTINUOUS 1. 2. 3. Countable Integer Value Observed Counted on hand Fraction or decimal Measured by an instrument Turn into discrete by rounding 8 Chapter 2 Chapter 2 Levels of Measurement Level of Measurement Nominal Ordinal Characteristics Example Categories only No avg Male, Female FR, SO, JR, SR Interval Ratio Rank has meaning No avg Distance has meaning Meaningful zero Chapter 2 Chapter 2 Temp (0 doesn’t mean no temp) Sales 9 Levels of Measurement (cont.) Types of Data Levels of Measurement Categorical (qualitative) Numerical (quantitative) Nominal Ordinal Interval Ratio Chapter 2 Chapter 2 10 Clicker Q Which kind of laptop do you own? – A.) Mac ­ 1 – B.) Dell ­ 2 – C.) HP ­ 3 – D.) None ­ 4 – E.) Other ­ 5 Chapter 2 Chapter 2 11 Clicker Q What kind of measurement was used for that question? – A.) Nominal – B.) Ordinal – C.) Interval – D.) Ratio Chapter 2 Chapter 2 12 Likert Scale Special case of Interval Data While values may not be numerical, intervals between are consistent Example… Surveymonkey.com Chapter 2 Chapter 2 13 Clicker Q How would you rate your cell phone service? – A.) Very Poor – B.) Poor – C.) Average – D.) Good – E.) Very Good Chapter 2 Chapter 2 14 Clicker Q What type of measurement was that? – A.) Nominal – B.) Ordinal – C.) Interval – D.) Ratio Chapter 2 Chapter 2 15 Time Series VS. Cross­ Sectional Time Series Cross­Sectional ­ single point in time – Variation among observations – GPAs of students in this class – Trends and patterns over time – Absenteeism Chapter 2 Chapter 2 16 Time Series example Chapter 2 Chapter 2 17 Sample or Census? Sample preferred 1. 2. 3. 4. Census preferred 1. 2. 3. 4. Infinite population Timely results Accuracy Cost Small population Large sample Database Laws Chapter 2 Chapter 2 18 Parameter vs. Statistic POPULATION Parameter: • Unknown • Fixed if pop stays same • N items SAMPLE Statistic: • Estimate for the parameter • Changes from sample to sample • n items Chapter 2 Chapter 2 19 Types of Samples Simple Random Sample (RANDBETWEEN(1,70)) Stratified Sample Cluster Sample – Reduces bias – SRS from strata or similar groups within a population – Geographical regions to define strata Chapter 2 Chapter 2 20 Nonrandom sample methods Judgment Sample Convenience Sample Both can lead to bias and should be avoided Chapter 2 Chapter 2 21 ...
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## This note was uploaded on 12/13/2010 for the course LEEDS BCOR 1020 taught by Professor Heatheradams during the Spring '08 term at Colorado.

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