Research in Tourism P1 - Statistics
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Questions and Answers

Which of the following is a disadvantage of matched sampling?

  • It requires a large sample size
  • It is cost-effective
  • It ensures a random sample
  • It may lead to biased results (correct)

Accidental sampling is a method that ensures a random sample is obtained.

False (B)

What is the primary method used in panel sampling?

Selecting a group randomly and asking for the same information multiple times

In quota sampling, the population is segmented into mutually exclusive __________.

<p>sub-groups</p> Signup and view all the answers

Match the sampling method with its description:

<p>Accidental Sampling = Sample drawn from readily available population Quota Sampling = Population segmented into exclusive sub-groups Line-intercept Sampling = Sampling based on chosen line segment intersecting elements Panel Sampling = Repeated measures from a randomly selected group</p> Signup and view all the answers

Which type of test is applied to data that are normally distributed?

<p>Parametric tests (D)</p> Signup and view all the answers

Non-parametric tests require a normal distribution to be applied.

<p>False (B)</p> Signup and view all the answers

What is the primary advantage of a simple random sample?

<p>It is free from bias.</p> Signup and view all the answers

The nominal level of measurement consists of _____, labels, or categories only.

<p>names</p> Signup and view all the answers

Match the sampling methods with their advantages:

<p>Simple Random Sample = Free from bias Systematic Random Sample = Easier to represent subgroups Non-parametric Tests = No normal distribution required Parametric Tests = Assumes normal distribution</p> Signup and view all the answers

Ordinal level data can be arranged in order and allows for meaningful differences between values.

<p>False (B)</p> Signup and view all the answers

What type of sampling involves selecting every nth individual from a numbered population?

<p>Systematic random sampling (B)</p> Signup and view all the answers

What is a disadvantage of sampling methods as mentioned in the content?

<p>It can introduce bias if the sample pattern matches the population pattern. (A)</p> Signup and view all the answers

What does non-probability sampling imply about the population elements?

<p>Some elements have no chance of selection.</p> Signup and view all the answers

Stratified sampling is beneficial as it yields less accurate results than simple random sampling.

<p>False (B)</p> Signup and view all the answers

What is the key characteristic of strata in stratified sampling?

<p>Homogeneous with respect to the given characteristic feature.</p> Signup and view all the answers

Snowball sampling is especially useful for studying __________ populations.

<p>low-incidence or rare</p> Signup and view all the answers

Match the sampling methods with their descriptions:

<p>Stratified Sampling = Samples drawn from homogeneous groups Snowball Sampling = Participants refer researchers to more subjects Cluster Sampling = Uses multiple stages to select sample units Matched Random Sampling = Assigning participants to groups based on characteristics</p> Signup and view all the answers

Which sampling method is described as less expensive and time-consuming?

<p>Cluster/Multistage Sampling (D)</p> Signup and view all the answers

Data at the interval level can only be arranged in random order.

<p>False (B)</p> Signup and view all the answers

What is the formula provided for calculating sample size with a population of N?

<p>N = N / (1 + NE^2)</p> Signup and view all the answers

What defines data at the ratio level of measurement?

<p>All of the above. (D)</p> Signup and view all the answers

Descriptive statistics is primarily concerned with making predictions about a population.

<p>False (B)</p> Signup and view all the answers

What is the primary goal of inferential statistics?

<p>Making inferences and drawing conclusions about a population.</p> Signup and view all the answers

________ sampling is also known as random sampling.

<p>Probability</p> Signup and view all the answers

Match the branches of statistics with their descriptions:

<p>Descriptive statistics = Summarization and description of data sets Inferential statistics = Making predictions based on sample data</p> Signup and view all the answers

Which of the following is true about sampling?

<p>Sampling helps in making inferences about the whole population. (D)</p> Signup and view all the answers

Data at the interval level of measurement has a natural zero point.

<p>False (B)</p> Signup and view all the answers

In statistics, the process of obtaining data and interpreting them is defined as __________.

<p>research</p> Signup and view all the answers

Flashcards

Statistics

The science of collecting, organizing, analyzing, and interpreting data to draw conclusions.

Descriptive Statistics

Deals with summarizing and describing existing data, focusing on patterns and trends.

Inferential Statistics

Makes inferences and draws conclusions about a population based on a sample. It's about using data to make predictions or decisions.

Sample

A subset of a population that is chosen to represent the whole group.

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Sampling

A process of selecting individuals from a population to make inferences about the whole group.

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Probability Sampling

Every individual in the population has an equal chance of being selected for the sample.

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Ratio Level of Measurement

Data has a natural zero point, and differences and ratios are meaningful. For example, temperature measured in Celsius.

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Ordinal Level of Measurement

Data can be ordered, but differences are not meaningful. For example, ranking of favorite movies.

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Convenience Sampling

A sampling method where participants are selected based on their proximity and convenience. It's often used for pilot testing.

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Parametric Tests

Statistical tests that require data to be normally distributed, usually with interval or ratio scale of measurement.

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Quota Sampling

A sampling technique that divides the population into groups based on shared characteristics (like age or gender) and then selects participants from each group based on a predetermined proportion. The selection within each group is not random.

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Non-Parametric Tests

Statistical tests that don't need normally distributed data, suitable for nominal or ordinal data.

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Mechanical Sampling

A sampling approach used for materials like solids, liquids, or gases, where devices like grabs, scoops, or probes are used to collect samples.

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Simple Random Sample

A type of sampling where each member of the population has an equal chance of being chosen.

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Line-Intercept Sampling

A sampling technique where a line is drawn across a region, and any element intersected by the line is included in the sample. It's used to estimate the proportion of elements in a specific area.

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Panel Sampling

A sampling method where a group of participants is initially selected randomly, and then the same group is surveyed multiple times over a period of time. This allows for tracking changes in opinions or behaviors.

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Systematic Random Sample

A sampling method where every nth member of the population is chosen, after starting at a random point.

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Nominal Level of Measurement

Data that can be categorized, but the order is not meaningful. For example, hair color (blonde, brown, black).

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Interval Level of Measurement

Data where the differences between values are meaningful. For example, temperature.

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Stratified Sampling

Sampling technique where the population is divided into subgroups (strata) based on a shared characteristic. Then, random samples are drawn from each stratum.

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Multistage Sampling

A sampling method where units are selected in stages, including aspects of random, stratified, and cluster sampling. It's like nested boxes, with different sampling methods applied at each level.

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Snowball Sampling

Sampling method where the researcher starts with one individual in the population of interest and asks them to refer others in the same population. This chain continues until enough participants are reached.

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Bias in Sampling

A type of biased sampling where the pattern in the sample selection aligns with the pattern in the population. This can lead to inaccurate results.

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Simple Random Sampling

Sampling technique where every element in the population has an equal chance of being selected. This is the basis of many statistical methods.

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Population Size (N)

The population size in a statistical analysis, often denoted by 'N'.

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Sample Size (n)

The sample size used in a study, often denoted by 'n'. It's a subset of the population.

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Study Notes

Research in Tourism P1 - Statistics

  • Statistics is the science of planning studies, experiments, obtaining, organizing, summarizing, presenting, analyzing, and interpreting data.
  • Branches of Statistics:
  • Descriptive statistics: Summarizes and describes data sets.
  • Inferential statistics: Makes inferences and draws conclusions from samples to make generalizations about populations.
  • Parametric vs. Non-parametric tests:
  • Parametric tests: Used for normally distributed data (interval or ratio scale) with assumptions about population distribution. Test significance and relationships.
  • Non-parametric tests: Used for data without normal distribution (nominal or ordinal scale), doesn't assume any specific population distribution. Tests significance when parametric assumption is violated.
  • Levels of Measurement:
  • Nominal: Names, labels, or categories, cannot be ordered.
  • Ordinal: Categories can be ordered, but differences between values aren't meaningful.
  • Interval: Data can be ordered, differences between values are meaningful, but there's no true zero point.
  • Ratio: Data can be ordered, differences and ratios are meaningful, there is a true zero point.
  • Sampling: Selecting a subset of a population to make inferences about the whole.
  • Probability sampling (random sampling): Every member of the population has an equal chance of being selected.
  • Simple random sampling: Every possible sample of the same size has an equal chance of being selected.
  • Systematic random sampling: Selecting every nth member of the population.
  • Stratified sampling: Dividing population into groups (strata) and randomly sampling from each strata.
  • Cluster sampling: Dividing population into clusters and randomly selecting clusters to sample.
  • Non-probability sampling: Some members of the population have no chance of selection or the probability of selection cannot be determined. Sampling errors cannot be estimated.
  • Accidental/Convenience sampling: Choosing readily available subjects.
  • Quota sampling: Selecting subjects based on predetermined proportions.
  • Judgment/Purposive sampling: Selecting subjects based on researcher's judgment.
  • Other Sampling Methods:
  • Snowball sampling: Identifying members of a population by referrals from one member to another.
  • Criterion sampling: Selecting participants who meet certain predetermined criteria.
  • Sampling Methods for Qualitative Studies:
  • Extreme case sampling: Selecting unusual or extreme cases.
  • Maximum variation sampling: Selecting participants with diverse characteristics.
  • Homogenous sampling: Selecting participants with similar characteristics.
  • Typical case sampling: Selecting cases that represent average or typical cases.
  • Critical case sampling: Selecting cases that are crucial for understanding a phenomenon.

Statistical Tools

  • Parametric tests: Assumes known population, data based on a known distribution, appropriate for continuous variables. Results are more powerful.
  • Non-parametric tests: Doesn't assume known about population, data can be arbitrary, applies to both continuous and discrete variables. Results are less powerful.

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TOU 028 - Research in Tourism P1 PDF

Description

This quiz explores essential concepts in statistics, including descriptive and inferential statistics, levels of measurement, and the differences between parametric and non-parametric tests. Test your understanding of how data can be collected, analyzed, and interpreted in the context of tourism research.

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