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STAT 1000 - Midterm 1 Exam Questions and Answers Already Passed

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STAT 1000 - Midterm 1 Exam Questions and Answers Already Passed population - Answers the entire group of items/individuals (units) about which we want information census - Answers a special case when every unit in the population is measured or surveyed (ex. US census) sample - Answers a small part of the population that we actually examine in order to gather information sampling frame - Answers the (best) list of items or people forming a population from which a sample is taken sampled population - Answers the collection of all possible observation units that might have been chosen in a sample; the population from which the sample was taken parameter - Answers a (numerical) summary of a variable for the entire population (typically unknown) statistic - Answers a (numerical) summary of a variable for a sample (used to estimate for the population) statistical inference - Answers generalizing the results from a sample to the population bias - Answers tendency of an estimate to deviate in one direction from a true value selection bias - Answers occurs when the sample is non-representative of the larger population of interest (best way to avoid this is by using randomness) simple random sampling (SRS) - Answers a sampling strategy in which every unit in the population is assigned a number and a random number generator selects which units will be used in the sample stratified sampling - Answers a sampling strategy in which the population is divided into groups based on a certain factor, each unit in the groups is given a number, and then a random number generator selects which units from each group will be used in the sample cluster sampling - Answers a sampling strategy in which units are already in random groups and when a group is selected, all of the units are used in the sample systematic sampling - Answers a sampling strategy in which the sample is obtained by selecting every kth individual (k is usually calculated as population size/sample size) multi-stage sampling - Answers a sampling strategy in which several stages of sampling are carried out (useful for large-scale sampling) sampling error - Answers the error that results from using a sample to estimate information regarding a population; cannot be avoided but can be minimized by using a large, representative sample non-sampling error - Answers the error that results from deficiencies in the survey process (poor sampling method, questionnaire wording, behavioral effects, etc.) non-response bias - Answers a non-sampling error that occurs when individuals selected by researchers decline/are not available to be part of the sample response bias - Answers a non-sampling error that occurs when individuals respond differently from how they truly feel (to avoid judgement, to look good, etc.) undercoverage - Answers a non-sampling error that occurs when the sampling frame excludes some parts of the population convenience sampling - Answers a non-sampling error that occurs when the most convenient (readily available) group is considered as the sample volunteer response sampling - Answers a non-sampling error that occurs when only those people who volunteer to participate are included in the sample variable - Answers characteristic associated with the cases in the data (what is being recorded) cases - Answers the objects described by a set of data (ex. customers, companies, experimental subjects, or other objects) categorical variable - Answers variable that places a unit into one of several groups or categories quantitative variable - Answers variable that takes numeric values for which arithmetic operations such as adding and averaging make sense graphical summaries for categorical variables - Answers pie charts and bar graphs graphical summaries for quantitative variables - Answers histogram, time plots, and scatterplots shape of a distribution - Answers skewed right (long tail to right), skewed left (long tail to left),

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STAT 1000 - Midterm 1 Exam Questions and Answers Already Passed

population - Answers the entire group of items/individuals (units) about which we want information

census - Answers a special case when every unit in the population is measured or surveyed (ex. US
census)

sample - Answers a small part of the population that we actually examine in order to gather information

sampling frame - Answers the (best) list of items or people forming a population from which a sample is
taken

sampled population - Answers the collection of all possible observation units that might have been
chosen in a sample; the population from which the sample was taken

parameter - Answers a (numerical) summary of a variable for the entire population (typically unknown)

statistic - Answers a (numerical) summary of a variable for a sample (used to estimate for the
population)

statistical inference - Answers generalizing the results from a sample to the population

bias - Answers tendency of an estimate to deviate in one direction from a true value

selection bias - Answers occurs when the sample is non-representative of the larger population of
interest (best way to avoid this is by using randomness)

simple random sampling (SRS) - Answers a sampling strategy in which every unit in the population is
assigned a number and a random number generator selects which units will be used in the sample

stratified sampling - Answers a sampling strategy in which the population is divided into groups based
on a certain factor, each unit in the groups is given a number, and then a random number generator
selects which units from each group will be used in the sample

cluster sampling - Answers a sampling strategy in which units are already in random groups and when a
group is selected, all of the units are used in the sample

systematic sampling - Answers a sampling strategy in which the sample is obtained by selecting every
kth individual (k is usually calculated as population size/sample size)

multi-stage sampling - Answers a sampling strategy in which several stages of sampling are carried out
(useful for large-scale sampling)

sampling error - Answers the error that results from using a sample to estimate information regarding a
population; cannot be avoided but can be minimized by using a large, representative sample

non-sampling error - Answers the error that results from deficiencies in the survey process (poor
sampling method, questionnaire wording, behavioral effects, etc.)

, non-response bias - Answers a non-sampling error that occurs when individuals selected by researchers
decline/are not available to be part of the sample

response bias - Answers a non-sampling error that occurs when individuals respond differently from
how they truly feel (to avoid judgement, to look good, etc.)

undercoverage - Answers a non-sampling error that occurs when the sampling frame excludes some
parts of the population

convenience sampling - Answers a non-sampling error that occurs when the most convenient (readily
available) group is considered as the sample

volunteer response sampling - Answers a non-sampling error that occurs when only those people who
volunteer to participate are included in the sample

variable - Answers characteristic associated with the cases in the data (what is being recorded)

cases - Answers the objects described by a set of data (ex. customers, companies, experimental subjects,
or other objects)

categorical variable - Answers variable that places a unit into one of several groups or categories

quantitative variable - Answers variable that takes numeric values for which arithmetic operations such
as adding and averaging make sense

graphical summaries for categorical variables - Answers pie charts and bar graphs

graphical summaries for quantitative variables - Answers histogram, time plots, and scatterplots

shape of a distribution - Answers skewed right (long tail to right), skewed left (long tail to left),
symmetric (major cluster in the middle)

modality - Answers number of peaks on a histogram

outliers - Answers unusual values that do not fit with the rest of the pattern (may result from data entry
errors or could be actual unusual values)

sample mean - Answers x-bar = sum of observations/number of observations; greatly impacted by
skewed data

median - Answers midpoint of a distribution

quartiles - Answers used to make box plots; Q1 = median of lower half of data, Q2 = median of data, Q3
= median of upper half of data

inter-quartile range - Answers calculated by subtracted Q1 from Q3; observations are considered
outliers if they are 1.5 x this amount

Información del documento

Subido en
20 de junio de 2025
Número de páginas
6
Escrito en
2024/2025
Tipo
Examen
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