Statistics for Managers Using Microsoft Excel - Ch 1 Terms
ratio scale of measurement
Highest form of measurement and meets all of the rules of other forms of measurement; - mutually exclusive categories, - exhaustive categories, - ordered ranks, - equally spaced intervals, and a - continuum of values
Types of Probability Samples
simple random sample, systematic stratified random sample, cluster (area) sample
Datum
singular form of data
population parameter
summarizes the value of a specific variable for a population only use with population
sample statistic
summarizes the value of a specific variable for sample data
secondary sources of data - collected from ongoing business activities
- bank studies years of financial transactions to help them identify patterns of fraud - economists utilize data on searches done via Google to help forecast future ecomomic conditions - marketing companies use tracking data to evaluate the effectiveness of a website - often large quantities of data
primary sources of data - observational studies and designed experiments have a common objective
- both attempt to quantify the effect that a process change/ treatment has on a variable of interest - observational study: no direct control over which items receive the treatment (dont mess with the participant) - designed experiment: direct control over which items receive the treatment (control what the participant sees in survey)
secondary sources of data arises from the following activities
- capturing data generated by ongoing business activities - distributing data compiled by an organisation or individual - most easy to access
primary sources of data arises from the following activities
- compiling responses from a survey - conducting a designed experiment and recording the outcomes - conducting an observational study and recording the results - takes longer to collect data
secondary sources of data - distributed by an organization or individual
- financial data on a company provided by investment services - industry or market data from market reseach firms and trade associations - stock prices, weather conditions, and sports statistics in daily newspapers - journal articles, reports, research - births, deaths, car registrations unemployment, etc. from ABS
primary sources of data - examples of data collected from observational studies
- focus groups elicit unstructured responses to open ended questions - measuring the time it takes for customers to be served - measuring the volume of traffic through an intersection to determine if advertising at an intersection is justified
primary sources of data - survey data
- investigation about the characteristics of a given population by - collecting data from a sample of that population - estimating their characteristics through the systematic use of statistical methodology - market research survey asking ppl what detergent they use - political polls of registered voters during political campaigns --> results turned around quickly - ppl being surveyed to determined their satisfaction with a recent product or service experience
primary sources of data - benefits of survey data
- mailed out, face to face, online, phone - short, concise, and quick
simple random sample
- type of probability sample - every individual or item from the frame has an equal chance of being selected - selection may be * with replacement (returned to frame for possible re-selection) * without replacement (isnt returned to the frame) - sample obtained from table of random numbers or computer
primary sources of data - data collected from observational studies
- watch and record information - consider biases when interpreting and drawing conclusions - not as clean as you may expect - interacting with consumers results in an impact on their behaviour
ratio scale data
A true zero origin exists Example: weight, age, heights, money spent, miles traveled, number of kids in household
Categorical Variable (Qualitative)
Any variable that is not quantitative is categorical. Categorical variables have no numerical meaning. Examples: yes/ no, Hair color, gender, field of study
Discrete Variable (Quantitative)
Arise from counting process e.g. number of text messages sent today
Continuous variable (Quantitative)
Arise from measuring process e.g. international units, minutes, kilometres e.g. how long it takes to...
ordinal scale of measurement
Classifies data into distinct categories Ranking is implied e.g. first, second, third
Population
Contains all of the items or individuals of interest that you seek to study Full census
ordinal scale of measurement
Data are assigned to categories that can be ranked with this type of measurement.
Sampling vs. Population
Less time consuming Less costly Less cumbersome and more practical than analysing entire population Consider consequences of cutting corners
Nominal scale of measurement
Lowest of the four levels of measurement Categories that are not more or less, but are different from one another in some way Mutually exclusive and exhaustive categories Named categories Example: Gender 1 = Male 2 = Female
sampling frame error
Occurs when certain sample elements are not listed or are not accurately represented in a sampling frame.
interval scale
Ordered scale Difference between measurements is a meaningful quantity Measurements do not have a true zero point
Data
Plural noun
Types of sampling
Probability sampling and non-probability sampling
interval scale data
Rating scales for subjective measures where distance is normally defined as one scale unit Example: Taste scale from 1 to 5, temperature Celsius, standardised scores
Destructive Testing
Test methods used to examine an object, material, or system causing permanent damage to its usefulness. Destroy what you are sampling = high cost
primary source of data
The data collector is the one using the data for analysis - political survey - an experiment - observed data
secondary source of data
The person performing data analysis is not the data collector - analyzing census data - examining data from journals and internet
Sampling
The process of selecting representative units from a total population Allow you to characterise and make inferences about ALL of something based on looking at PART of it
Numerical Variables (Quantitative)
Values that represent a counted or measured quantity
sampling frame
a list of the items or people forming a population from which a sample is taken.
Sample
a part of the population that we actually examine in order to gather information
ordinal scale
a scale of measurement in which the measurement categories form a rank order along a continuum
types of non-probability sampling
convenience, judgement, quota, snowball focus on convenience and judgement
Frames
data sources such as population lists, directories, or maps
Judgment sampling
get the opinions of preselected experts in the subject matter OR use one or more SME's to select the sample
Nominal scale of measurement
is a categorical measurement classifies data into distinct categories in which no ranking is implied e.g. - what is your favorite soft drink, - your political party affiliation, and - your gender.
probability sample
items in the sample are chosen on the basis of the known probabilities
non-probability sample
items included are chosen without regard to their probability of occurrence
convenience sampling
selects items based only on the fact that they are - easy - inexpensive, or - convenient to sample
