Chapter 1

Question 0

Statistical Inference Procedures

Answer 0

Procedures that allow a decision maker to reach a conclusion about a set if data based on a subset of that data. TWO Primary categories: Estimation & Hypothesis.

Question 1

Business Statistics

Answer 1

A collection of procedures and techniques that are used to convert data into meaningful information in a business environment

Question 2

Statistical Inference Procedure: ESTIMATION

Answer 2

In situations in which we would like to know about all the data in a large data set but it’s impractical to work with all the data; The estimates are formed by looking closely at a subset of the larger data set.

Question 3

Statistical Inference Procedures: HYPOTHESIS

Answer 3

Hypothesis testing uses statistical techniques to validate a claim.

Question 5

Experiment

Answer 5

An experiment is any process that generates data as its outcome, whose results cannot be predicted with certainty.

Question 5

Closed-Ended Questions

Answer 5

Questions that require the respondent to select from a short list of defined choices.

Question 6

Experimental Design

Answer 6

The plan for performing the experiment in which the variable of interest is defined is referred to as an experimental design. In the experimental design one or more factors are identified to be changed so that the
impact on the variable of interest can be observed or measured.

Question 7

Open-Ended Questions

Answer 7

Questions that allow respondent the freedom to respond with any value, words, or statements of their own choosing.

Question 8

Demographic Questions

Answer 8

Questions relating to the respondents’ characteristics, background and attributes.

Question 9

Structured Interview

Answer 9

Interviews in which the questions are scripted.

Question 10

Unstructured Interview

Answer 10

Interviews that begin with one or more broadly states questions with further questions being based on the responses.

Question 11

Direct Observation

Answer 11

A procedure used to collect data, the procedure requires the process from which the data are being collected to be physically observed and the data recorded based on what takes place in the process.

Question 12

Bias

Answer 12

An effect that alters a statistical result by systematically distorting it; different from a random error, which may distort on any one occasion but balances out on he average.

Question 13

DATA COLLECTION ISSUES

Answer 13

• Data Accuracy
• Interviewer Bias
• Non Response Bias
• Observer Bias
• Selection Bias
• Measurement Error
• Internal Validity
• External Validity

Question 14

Selection Bias

Answer 14

Bias interjected through the way subjects are selected for data collection.

Question 15

Observer Bias

Answer 15

Data collection through personal behaviour is also subject to problems. People tend to view the same event or item differently. This is referred to as observer bias.

Question 16

Internal Validity

Answer 16

A characteristic of an experiment in which data are collected in such a way as to eliminate the effect of variables within the experimental environment that are not of interest to the researcher.

Question 17

External Validity

Answer 17

A characteristic of an experiment whose results can be generalized beyond the test environment so that the outcomes can be replicated when the experiment is repeated.

Question 18

Population

Answer 18

the set of all objects or individuals of interest or the measurements obtained from all objects or individuals of interest.

Question 19

Sample

Answer 19

a subject of the population

Question 20

Census

Answer 20

an enumeration of the entire set of measurements taken from the whole population

Question 21

Statistical Sampling Techniques:

Answer 21

those sampling methods that use selection techniques based on chance selection

Question 22

Non-Statistical Sampling Techniques

Answer 22

Those methods of selecting samples using convenience, judgement or other non chance processes

Question 23

Convenience Sampling

Answer 23

a sampling technique that selects the items from the population based on accessibility and ease of selection

Question 24

Frame

Answer 24

the list of all objects or individuals in the population

Question 25

Parameters

Answer 25

descriptive numerical measures, such as an average or a proportion, that are computed from an entire population

Question 26

Statistic

Answer 26

corresponding measures for a sample

Question 27

Statistical sampling methods

Answer 27

also called probability sampling, allow every item in the population to have a known or calculable chance of being included in the sample

Question 28

Statistic Sampling Methods

Answer 28

the fundamental statistical sampling method is called a SIMPLE RANDOM SAMPLING , other types of statistical sampling methods are STRATIFIED RANDOM SAMPLING, SYSTEMATIC SAMPLING AND CLUSTER SAMPLING

Question 29

Simple Random Sampling

Answer 29

A method of selecting items from a population such that every possible sample of a specified size has an equal chance of being selected

Question 30

Stratified Random Sampling

Answer 30

a statistical sampling method in which the population is divided into subgroups called strata, so that each population item belongs to only one stratum. The objective is to form a strata such that the population values of interest within each stratum are as much alike as possible. Sample items are selected from each stratum using the simple random sampling methods

Question 31

Systematic Random Sampling

Answer 31

a statistical sampling technique that involves selecting every Kth item in the population after a randomly selected starting point between 1 and K. The value of K is determined as the ratio of the population size over the desired sample size

Question 32

Cluster Sampling

Answer 32

a method by which the population is divided into groups or clusters that are each intended to be mini-populations. A simple random sample of a cluster can be selected using any probability sampling technique

Question 33

Quantitive data

Answer 33

measurements whose values are inherently numberical

Question 34

Qualitative data

Answer 34

data whose measurements scale is inherently categorical

Question 35

Time Series data

Answer 35

a set of consecutive data values observed at successive points in time

Question 36

Cross-sectioned data

Answer 36

a set of data values observed at a fixed point in time

Question 37

DATA MEASUREMENTS LEVELS

Answer 37

• Nominal data
• Ordinal data
• Interval data
• Ratio data

Question 38

Nominal data

Answer 38

the lowest form of data, assigning codes to categories generates nominal data. Values given to categories that have no specific meaning are nominal data, because the order of the categories is arbitrary. With NOMINAL data, we also have complete control over what codes are used

Question 39

Ordinal data

Answer 39

ORDINAL or rank data are one notch above nominal data on the measurement hierarchy. At this level, the data elements can be rank-ordered on the basis of some relationship among them, with the assigned values indicating this order

Question 40

Interval data

Answer 40

if the distance between two data items can be measured on some scale and the data have ordinal properties (>,<,=) the data are said to be interval data. Best example is TEMPERATURE

Question 42

Ratio data

Answer 42

data that have all the characteristics of interval data but also have a zero point (at which means “none”) are called RATIO data. Ratio measurements is the highest level of measurements. Weight is a good example of RATIO data.