BIO1109 Biostatistics: Sampling Bias

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Questions and Answers

What is one potential source of bias in sampling?

Omitting hard-to-reach groups (correct)

Utilizing a diverse sample frame

Using a state-of-the-art sampling technique

Increasing response rates

At which step of the scientific method is a hypothesis generated?

Before formulating research questions

When collecting data

During data analysis

After making an observation (correct)

Which of the following methods could reduce sampling bias?

Replacing individuals difficult to contact

Expecting low response rates

Using an updated sample frame (correct)

Deviating from pre-agreed sampling rules

What characterizes a scientifically sound hypothesis?

It is based on extensive background research Signup and view all the answers

Which of the following is NOT a recognized potential source of bias in sampling?

Use of current and comprehensive lists Signup and view all the answers

In the scientific method, what is the primary purpose of making an observation?

To formulate questions based on uncertainties Signup and view all the answers

What can happen if a sample frame is outdated in sampling methods?

Sample may exclude recently moved individuals Signup and view all the answers

What is an important aspect of a hypothesis in scientific research?

It should allow for quantitative predictions Signup and view all the answers

What is the primary purpose of biostatistics?

To analyze data derived from biological sciences and medicine Signup and view all the answers

Which of the following can be classified as a quantitative variable?

The number of website visits per day Signup and view all the answers

Which term describes a variable whose values arise from chance factors?

Random Variable Signup and view all the answers

What is not a common source of data in biostatistics?

Personal anecdotes Signup and view all the answers

Which of the following statements about discrete random variables is accurate?

They have gaps or interruptions in the values that they can assume. Signup and view all the answers

What type of data does biostatistics primarily deal with?

Numbers derived from measurements and counting Signup and view all the answers

Which characteristic defines a qualitative variable?

It categorizes individuals based on attributes. Signup and view all the answers

From where can data be sourced for biostatistical analysis?

Routinely kept records, surveys, and experiments Signup and view all the answers

What characterizes a continuous random variable?

It can assume any value within a specified interval. Signup and view all the answers

What is the simplest definition of a population in biostatistics?

The largest collection of entities or values of interest. Signup and view all the answers

Which measurement scale allows for ranking but does not provide the distance between ranks?

Ordinal scale Signup and view all the answers

In which measurement scale are observations classified into mutually exclusive categories without any order?

Nominal scale Signup and view all the answers

What distinguishes the interval scale from the nominal scale?

The interval scale defines the exact distance between values. Signup and view all the answers

Which of the following is NOT an example of a measurement scale?

Statistical scale Signup and view all the answers

What can be defined as a part of a population?

Sample Signup and view all the answers

Which of the following measurement scales has the highest level of sophistication?

Ratio scale Signup and view all the answers

What characterizes the ratio scale of measurement?

It allows determination of both equality of ratios and equality of intervals. Signup and view all the answers

Which of the following is an example of a trait typically measured using the ratio scale?

Height Signup and view all the answers

What is the main purpose of statistical inference?

To estimate characteristics of a population based on a sample. Signup and view all the answers

Which method is NOT a type of probability sampling?

Judgment sampling Signup and view all the answers

What defines simple random sampling?

Every member of the population has a known chance of selection. Signup and view all the answers

How is systematic sampling conducted?

Every x/nth individual is selected from a list. Signup and view all the answers

Which statement is true regarding probability sampling methods?

They involve randomness in selecting samples. Signup and view all the answers

What distinguishes non-probability sampling from probability sampling?

It does not allow every member a chance of selection. Signup and view all the answers

Which of the following is a feature of stratified random sampling?

It ensures that subgroups are represented in the sample. Signup and view all the answers

What is a primary disadvantage of convenience sampling?

It can lead to significant bias in results. Signup and view all the answers

Which sampling method selects whole subgroups, or clusters, for inclusion in the study?

Clustered sampling Signup and view all the answers

What is the main characteristic of non-probability sampling methods?

Participants are chosen based on specific criteria. Signup and view all the answers

In probabilistic sampling methods, which method ensures that every individual has an equal chance of being selected?

Simple random sampling Signup and view all the answers

Why might stratified random sampling be preferred over simple random sampling?

It decreases variability by ensuring all subgroups are included. Signup and view all the answers

Which of the following sampling methods is most likely to generate biased results?

Convenience sampling Signup and view all the answers

What does clustered sampling primarily use as the sampling unit?

Clusters Signup and view all the answers

Study Notes

Bias in Sampling

Five key sources of sampling bias must be considered when selecting samples, regardless of the method used.
Deviating from pre-established sampling rules can introduce bias.
Hard-to-reach demographics may be excluded from samples.
Replacing selected individuals can lead to unrepresentative samples.
Low response rates can skew the results, impacting the validity of findings.
Using outdated sample frames can omit recent movers and create bias.

The Scientific Method

A systematic approach to collecting, analyzing, and reporting scientific data to yield unbiased, replicable results.
Step 1: Making an Observation - Focus on a phenomenon leading to scientifically testable questions.
Step 2: Formulating a Hypothesis - Develop hypotheses to explain observations, often involving extensive background research.

Basic Concepts in Biostatistics

Data is defined as numbers and is the foundation of statistical analysis.
Statistics involves the collection, organization, summarization, analysis of data, and drawing inferences from samples.
Sources of data can include routinely collected records, surveys, experiments, and external sources.
Biostatistics specializes in data from biological sciences and medicine.

Types of Variables

A variable represents characteristics that can assume different values across individuals or situations.
Quantitative Variables are measurable (e.g., height, weight).
Qualitative Variables categorize individuals or objects based on attributes (e.g., ethnicity).
Random Variables produce values impacted by chance, while Discrete Random Variables have gaps in possible values.
Continuous Random Variables can take any value within a range.

Sampling and Inference

Statistical inference concludes about a population based on a sample.
Sampling strategies are divided into probability and non-probability methods.

Probability Sampling Methods

Simple Random Sampling: Every subset of the population has an equal chance of selection.
Systematic Sampling: Individuals are selected at regular intervals from the sampling frame (e.g., every nth individual).
Stratified Random Sampling: Population divided into subgroups (strata) to ensure representation of different characteristics.
Clustered Sampling: Entire clusters are randomly chosen as sampling units instead of individual members.

Non-Probability Sampling Methods

Convenience Sampling: Participants selected based on availability; while easy, it risks significant bias since volunteers may differ from non-volunteers.
Quota Sampling: Ensures specific characteristics in the sample mirror the population.
Judgement (Purposive) Sampling: Researchers select participants based on specific criteria.
Snowball Sampling: Existing subjects recruit future subjects, useful for hard-to-reach populations but risks bias due to non-random selection.

Measurement and Measurement Scales

Measurement assigns numbers to objects or events according to defined rules.
Nominal Scale: Classifies observations into distinct categories without order.
Ordinal Scale: Ranks categories with an implied order.
Interval Scale: Values have defined distances between them but lack a true zero.
Ratio Scale: Highest measurement level with a true zero, allowing for comparison of ratios.

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Description

This quiz covers key concepts of sampling and statistical inference as outlined in the BIO1109 Biostatistics course. The focus is on understanding the various sources of bias that can affect sample selection. Test your knowledge of these critical issues to ensure accurate research methodologies in health sciences.