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2. QU1 > QU1 Chapter 1 > Flashcards

QU1 Chapter 1 Flashcards

1
Q

Why does a manager need to know about statistics

A
  1. to know how to properly present information
  2. to know how to draw conclusions about populations based on sample information
  3. to know how to improve processes
  4. to know how to obtain reliable forecasts
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2
Q

What is the growth of development of modern stats?

A
  1. needs of government to collect data on its citizenry
  2. which lead to the development of the mathematics of probability theory
  3. the evolution of electronic computing
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3
Q

definition of population:

A

(universe) is a collection of things under consideration

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4
Q

Definition of sample

A

portion of the population elected for analysis

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5
Q

definition of parameter

A

summary measure computer to describe a characteristic of the population

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6
Q

definition of statistic

A

summary measure computed to describe a characteristic of the sample

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7
Q

definition: descriptive statistics

A

collection, presentation and characterization of data

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8
Q

Definition: Inferential Statistics

A

estimation of a characteristic of a population or drawing conclusions concerning a population based only on sample results.

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9
Q

What is descriptive Statistics - eData collection, presentation and characterization

A

data collection - survey
data presentation - tables and graphs
data characterization - eg. sample mean

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10
Q

describe mean average and

A

need more

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11
Q

Describe inferential statistics

A

estimation - eg. estimate the population mean weight using the sample mean weight
Hypothesis testing - eg. test the claim that the population mean weight is 120 pounds
(draw conclusions and /or making decisions concerning a population based on sample results)

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12
Q

Why is data needed?

A
  1. to provide input to survey
  2. to provide input to study
  3. to measure performance of service or production process
  4. to evaluate conformance to standards
  5. to assist in formulating alternative courses of action
  6. to satisfy curiosity
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13
Q

What are the two data sources

A
  1. primary data collection

2. Secondary data compilation

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14
Q

What does primary data collection consist of

A
  1. observation
  2. Survey
  3. experimentation
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15
Q

what does secondary data compilation consist of

A

print or electronic

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16
Q

what is a random variable

A

definition of possible outcomes of interest form an experiment

17
Q

what are the types of random variables

A
  1. categorical (qualitative)

2. Numerical (quantitative)

18
Q

What are the two types of numerical (quantitative)

A
  1. Discrete (counting)

2. Continuous (Measuring)

19
Q

what are the reasons why we want to draw a sample

A
  1. less time consuming than a census
  2. less costly than a census
  3. less cumbersome and more practical to administer than a census of the targeted population
20
Q

What are the types of sampling methods

A
  1. Non-probability samples

2. Probability samples

21
Q

what are the probability samples

A
  1. simple random
  2. systematic
  3. stratified
  4. cluster
22
Q

what are the Non-probability samples

A
  1. Judgement
  2. quota
  3. Chunk
23
Q

What is a simple random (watch a video) need more detail (replacement or replacement???)

A
  • every individual or item form the frame has an equal chance of being selected
  • selection may be with replacement or without replacement
  • samples obtained from a table of random number for computer random number generators
24
Q

What is systematic

A
  1. Decided on sample size : n
  2. divided frame of N individuals into groups of k individuals: k= N/n
  3. randomly select one individual from the 1st group
  4. select every k-th individual thereafter
25
Q

What is a stratified sample

A
  1. population divided into two or more groups according to some common characteristic
  2. simple random sample selected form each group
    the two or more samples are combined into one
26
Q

What is cluster

A
  1. population divided into several “Clusters” each representative of the population
  2. simple random sample selected from each
  3. the samples are combined into one
27
Q

what are the advantages and disadvantages of simple random sample

A
  • simple to use

- may not be a good representation of the population’s underlying characteristics

28
Q

what are the advantages and disadvantages of stratified sample

A

ensures representation of individuals across the entire population

29
Q

what are the advantages and disadvantages of cluster sample

A
  • more cost effective

- less efficient (need larger sample to acquire the same level of precision)

30
Q

what are some questions to ask when evaluating survey wrothiness

A
  1. what is the purpose of the survey
  2. is the survey based on probability sample?
  3. coverage error - appropriate frame?
  4. non-response error - followed up?
  5. measurement error - good questions elicit good responses
  6. sampling error - always exists. reduced by taking large samples
31
Q

what are the types of survey errors

A
  1. coverage error
  2. non response error
  3. sampling error
  4. measurement error
32
Q

what is coverage error

A

certain groups are excluded from the frame, therefore they have no chance of being included

33
Q

what is non response error

A
  • must follow up with non responses
34
Q

what is sampling error

A

chance differences form sample to sample

35
Q

what is measurement error

A

bad question, leading questions must be avoided
Halo effect
and respondent error - overzealous or under zealous efforts by the respondend

36
Q

what is data

A

data is a set of numbers that represent some type of metric or measurement

37
Q

what is information

A

information is what the data means

38
Q

Descriptive statistics according to cga

A

how data is organized, described and presented

  • statistics such as mean (average), variance, range etc.
  • organized and presented using tables, charts etc.
39
Q

Inferential statistics according to CGA

A

drawing conclusions about the population based on the sample’s data

2. QU1 (11 decks)

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