Business Statistics Terms

Descriptive statistics – methods that help collect, summarize, present and analyze a set of data

Inferential statistics – methods that use the data collected from a small group to draw conclusions about a larger group

Population – everything we are interested about which you want to draw a conclusion

Sample – part of a population (a portion)

Parameter – describes a characteristic of a population

Statistic – measure that describes a characteristic of a sample

Sampling frame – (population) listing of items that make up the population we wish to study

Nonprobability samples: chosen without regard to their probability of occurrence

1. Convenience sampling – based only on the fact they are easy, inexpensive, convenient to collect  

2. Judgement sampling – opinions from preselected groups (in your judgment, it is consistent to overall population

Probability samples – everyone has to have the probability/ opportunity

1. Simple random sample – everyone has an equal chance of being selected (names in a hat)

2. Systematic sample: used frequently in a continuous production process and requires data be in some type of order

3. Stratified sampling – divide population into 2 or more subgroups (strata) according to common characteristic
*sample size proportional to strata size

4. Cluster sampling –entire population is divided into clusters and a random cluster is selected (darts)

(Survey errors)
Coverage error/ selection bias – if some groups are excluded from the frame and have no chance of being selected

Nonresponse error/bias – people who do not respond may be different than ppl who respond

Sampling error – variation from sample to sample (flipping a coin)

Measurement error – weakness in question design, respondent error, interviewer’s effects

(Sources of Data)
1. Data collected & distributed by an organization/ individual (annual report, newspaper)

2. Designed experiment (1 half of class takes daily quiz, other doesn’t; all have to take final)

3. Survey (what do student’s think of tests?) [pic 1]

4. Observational study (arrival time of students in a classroom)

(Steps taken when using statistics)
1. Define the problem/sampling frame (make-up fake data)