BUAL 2600 Yan Final Exam 2023 with complete solution
Data
Facts and figures from which conclusions can be drawn
Data Set
The data that are collected for a particular study
Variable
any characteristic of an element
Quantitative Variables
The possible measurements of the values of a variable are numbers that represent
quantities
Ex: Age
Qualitative (Categorical) Variables
Labels or names used to identify an attribute of each element
Ex: Names, addresses, phone numbers
Cross Sectional Data
Data collected at. the same time or approximately the same time
Time Series Data
Data collected over different time periods
Population
A set of all elements about which we draw conclusions
Sample
A. subset of all the elements in a population
Probability Sampling
Sampling where we know the change that each element in the population will be
included in the sequence
convience sampling
sampling where we select elements because they are convenient to sample
not a probability sample
voluntary response sampling
samples in which participants self-select
-frequently used by radio and television
-over represent people with strong opinions
judgements sampling
samples in which a person who is extremely knowledgable about the population selects
population elements he or she feels are most representative
nominative variable
a qualitative variable for which there is no meaningful ordering, or ranking, of the
categories
Ex: gender, car color
ordinal variable
A qualitative variable for which there is a meaningful ordering or ranking of the
categories.
Ex: teaching effectiveness
interval variable
, All of the characteristics of ordinal (meaningful ranking) plus... measurements are on a
numerical scale with an arbitrary zero point and can only meaningfully compare values
by the interval between them
Ex: Temperature
ratio variable
interval plus Measurements are on a numerical scale with a meaningful zero point such
as anything related to money
Ex: Earnings, profit, loss, age, distance, height
stratified random sampling
divide population into non-overlapping groups (strata) then select a random sample
from each strata
multistage cluster sampling
divide population into clusters and then randomly select clusters to sample
systematic sampling
list population, select random starting point, sample each nth element
dichotomous questions
-clearly stated
-easy to answer
-easy to analyze
-limited information
multiple choice questions
-allow more than two responses
-usually analyzed with averages
open-ended questions
-most honest and complete information
-cannot be readily summarized
phone surveys
-inexpensive
-low response rate
mail surveys
-inexpensive
-low response rate (20-30%)
-requires multiple mailings
web surveys
-cheaper still
-same problems as mail surveys
personal interviews
-more expensive
-more control
-higher response rates
relative frequency
summarizes a proportion of items in each class
relative frequency for a class formula
(number of frequency of the class)/n
multiply by 100 to obtain percent frequency
bar chart
Data
Facts and figures from which conclusions can be drawn
Data Set
The data that are collected for a particular study
Variable
any characteristic of an element
Quantitative Variables
The possible measurements of the values of a variable are numbers that represent
quantities
Ex: Age
Qualitative (Categorical) Variables
Labels or names used to identify an attribute of each element
Ex: Names, addresses, phone numbers
Cross Sectional Data
Data collected at. the same time or approximately the same time
Time Series Data
Data collected over different time periods
Population
A set of all elements about which we draw conclusions
Sample
A. subset of all the elements in a population
Probability Sampling
Sampling where we know the change that each element in the population will be
included in the sequence
convience sampling
sampling where we select elements because they are convenient to sample
not a probability sample
voluntary response sampling
samples in which participants self-select
-frequently used by radio and television
-over represent people with strong opinions
judgements sampling
samples in which a person who is extremely knowledgable about the population selects
population elements he or she feels are most representative
nominative variable
a qualitative variable for which there is no meaningful ordering, or ranking, of the
categories
Ex: gender, car color
ordinal variable
A qualitative variable for which there is a meaningful ordering or ranking of the
categories.
Ex: teaching effectiveness
interval variable
, All of the characteristics of ordinal (meaningful ranking) plus... measurements are on a
numerical scale with an arbitrary zero point and can only meaningfully compare values
by the interval between them
Ex: Temperature
ratio variable
interval plus Measurements are on a numerical scale with a meaningful zero point such
as anything related to money
Ex: Earnings, profit, loss, age, distance, height
stratified random sampling
divide population into non-overlapping groups (strata) then select a random sample
from each strata
multistage cluster sampling
divide population into clusters and then randomly select clusters to sample
systematic sampling
list population, select random starting point, sample each nth element
dichotomous questions
-clearly stated
-easy to answer
-easy to analyze
-limited information
multiple choice questions
-allow more than two responses
-usually analyzed with averages
open-ended questions
-most honest and complete information
-cannot be readily summarized
phone surveys
-inexpensive
-low response rate
mail surveys
-inexpensive
-low response rate (20-30%)
-requires multiple mailings
web surveys
-cheaper still
-same problems as mail surveys
personal interviews
-more expensive
-more control
-higher response rates
relative frequency
summarizes a proportion of items in each class
relative frequency for a class formula
(number of frequency of the class)/n
multiply by 100 to obtain percent frequency
bar chart
