Question

____

Simple Random Sample

____

Cluster sample

____

Systematic sample

____

Stratified sample

1.

While this type of sampling is very eacy to carry out, and hence
saves time and money, it can very easily yield samples which are
non-representative of the population, unintentionally. Often, data
comes "in cycles", where the beginning and the end of each cycle is
"atypical". If the "kth" individual is picked at the beginning or
at the end of a cycle more often than a random individual, the
sample picked is non-representative.

2.

This type of sampling saves time and money, but can very easily
yield samples which are non-representative of the population,
unintentionally. One atypical "cluster" may yield a large
proportion of atypical individuals, so the sample becomes atypical
because only individuals from randomly selected clusters are picked
to become part of the sample.

3.

This type of sampling gives every individual an equal chance to be
picked and gives every sample of a given size an equal chance to be
picked - which is good- but at a great money and time investment.
In addition, all individuals in the population have to be known
before sampling can proceed. This is a problem when studying large
populations or populations of unknown size, for example,
earthworms.

4.

This type of sampling allows comparison of unequal size groups, or
insuring proportional representation of groups with low response.
However, determining a unique category for individuals may be
problematic, as in should a 1/2 African American/1/2 Asian
individual be counted as an African American? counted as both
African American and Asian? thrown out of the study?Throwing out
individuals equals non-response...

-----------

Please match the following "probability" samples types to their description.

____

Simple Random Sample (SRS)

____

Stratified Sample

____

Systematic Sample

____

Cluster Sample

1.

A sample in which all individuals in the population are numbered,
and random individuals from the population are picked using a
Random Number Generator or a Random Digit Table. It is like
randomly picking slips out of a hat, but that is impractical for
large populations.

2.

A sample which is picked by subdividing the populations into
(preferably diverse or heterogeneous) clusters, then picking a
random sample of the clusters, then subdividing the clusters picked
into smaller (preferably diverse) groups, picking a random sample
of groups, etc.

3.

A sample which is picked by numbering all individuals in the
population and then picking every "kth" individual, like giving the
questionnaire to every 17th customer who walks through the door of
a doctor's office.

4.

A sample which is picked by subdividing the population into
unambiguous uniform or homogeneous groups, then picking random
samples of these groups. The total random sample may give all
groups proportional representation or equal representation.

Answer #1

1. Simple random sample (SRS)

(Since,each individual in population has equal chance of being included)

2. Cluster sample

(Since, in cluster sampling divides population into heterogeneous groups and a simple random sample of groups selected)

3.Systematic sample

(Since,in systematic sampling one of the first k selected randomly then every kth individual selected in sample)

4.Stratified sample

(Since, in stratified sampling divides data into homogeneous groups called as strata and random sample is taken from each statum)

Identify the sampling strategy used in each scenario. Select
from simple random, systematic, stratified, cluster, convenience,
or state that this is not a random sampling strategy.
a. Names are written on ping-pong balls, then the balls are
mixed and drawn at random.
b. The population of those on campus are divided into students,
faculty, and staff. A proportional number are then randomly
selected using simple random sampling from each of the three
groups.
c. Individuals are lined up and every...

In a systematic sample a random starting point is chosen, and
Multiple Choice
Each item in the population has a chance of being selected more
than once
The population is divided into groups and then samples are drawn
from these groups
Each item in a list has a 50% chance of being selected
Every kth item thereafter is selected for the sample

Identify the type of sampling used: random, systematic,
convenience, stratified, or cluster.
To estimate the percentage of defects in a recent manufacturing
batch, a quality control manager at IBM selects every the 12th
computer that comes off the assembly line starting with the until
she obtains a sample of 90 computers

1a.) Stratified Random Sampling involves:
a. Dividing the population into overlapping groups
b. Taking a random sampling of a percentage of the pre-chosen
groups (usually 10% of total groups)
c. Choosing non-overlapping clusters (i.e. streets of a city)
and collecting data from all members of the selected cluster
d. None of the above
1b.) A data set consists of the values 2, 6, 3, and 1. If we
consider this a population (all the values available), the variance
is
a....

Classify each sample as Random, Systematic, Stratified, Cluster
or other?
All fast food workers at a randomly selected fast food
restaurants are selected and asked how many hours per week they
work.
Every 100th hamburger manufactured is checked to
determine its fat content.
Mail carriers of a large city are divided into four groups
according to gender (male or female) and according to whether they
walk or ride on their routes. Then 10 are selected from each group
and interviewed...

In stratified sampling, a random sample of subgroups is selected
and all members of the subgroups become part of the sample.
True
False
In stratified sampling, a random sample of subgroups is selected
and all members of the subgroups become part of the sample.
True
False
Non-probability sampling may not be representative of the
population, thus it does not allow the researcher to explicitly
identify possible biases.
True
False
The object of sampling is to obtain data that is representative...

A. Systematic Sample
B. Simple Random Sample
C. Convenience Sample
D. Multi-Stage Sample
E. Stratified Sample
F. Cluster Sample
1. Among your friends who took the exam, select 4 of them
completely at random.
2. Obtain an alphabetical list of
all students who took the exam. Starting with the 6th student on
the list, survey every 14th student.
3. Randomly choose 4 of the 14
sections, and survey every student from those 4 sections.
4. Choose a set of 42...

Five different sampling methods are described below.
Choose the one that defines stratified sampling.
1. Select members of a population by asking for volunteers, or
otherwise find a sample that is easy to obtain and is not based on
randomness or chance.
2. Order the population, select a random starting point and
interval, then select individuals every interval from the starting
point until the desired sample size is achieved.
3. Take a sample of size ?n from a population in...

1. The difference between a sample mean and the population mean
or the difference between the means of two random samples is
called: A. nonresponse error. B. selection bias. C. sampling error.
D. nonsampling error.
2. The manager of the customer service division of a major
consumer electronics company is interested in determining whether
the customers who have purchased a videocassette recorder over the
past 12 months are satisfied with their products. If there are 4
different brands of videocassette...

Match the following descriptions with the correct sampling
technique.
- A sample in which every group of n items is equally
likely.
A sample in which the population is divided into groups, and
then a random sample is taken from each.
- A sample in which every member has an equally likely chance of
selection.
- A sample where a few groups are randomly selected, and then
each member of those groups are measured.
- A sample where the first...

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