Biostatistics Introduction Quiz

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Questions and Answers

What is the primary concern of the field of statistics?

  • Collection, organization, summarization, and analysis of data (correct)
  • Creating complex algorithms
  • Primarily focusing on mathematical theories
  • Generating conclusions without data

Which term is used specifically when statistical tools are applied in biological sciences and medicine?

  • Data science
  • Mathematical statistics
  • Statistics
  • Biostatistics (correct)

Which of the following is NOT a source of data for biostatistical analysis?

  • Routinely kept records
  • External sources
  • Surveys
  • Random guesses (correct)

When might a survey be the appropriate source of data?

<p>When needing data about patients' transportation modes (B)</p> Signup and view all the answers

What type of data arises from counting or measuring?

<p>Raw data (A)</p> Signup and view all the answers

What is the primary characteristic of a discrete variable?

<p>It is characterized by gaps or interruptions in its values. (B)</p> Signup and view all the answers

Which of the following best describes a population in statistical terms?

<p>The complete set of values of a variable of interest. (A)</p> Signup and view all the answers

In which of the following situations would a qualitative variable be appropriate?

<p>Classifying people into socio-economic groups. (B)</p> Signup and view all the answers

What differentiates continuous variables from discrete variables?

<p>Continuous variables can assume any value within a specified relevant interval. (B)</p> Signup and view all the answers

Which of these is an example of a quantitative variable?

<p>The number of patients visiting a clinic. (B)</p> Signup and view all the answers

Flashcards

Biostatistics

The application of statistical tools and concepts to biological sciences and medicine.

Data

Figures resulting from counting or measurements, the raw material of statistics

Statistics

The collection, organization, summarization, analysis, and interpretation of data.

Population

The entire group of individuals or objects about which information is wanted.

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Sample

A subset of a population selected for study, used when studying the whole population is impractical or impossible.

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Variable

A characteristic that changes in value across different people, places, or things.

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Quantitative Variable

A variable that can be measured in a numerical way.

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Discrete Variable

A variable that can only take on specific values, no values in between

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Continuous Variable

A variable that can take on any value within a range.

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Population

The complete set of items or individuals of interest.

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Study Notes

Biostatistics Introduction

  • Biostatistics applies statistical methods to biological data, particularly in medicine and healthcare.
  • Key terms include: Statistics, data, Biostatistics, Variable, Population, Sample
  • Statistics is the collection, organization, summarization, and analysis of data.
  • Statisticians interpret and communicate findings to others.
  • Inferences are drawn about large data sets when only a portion of the data is observed.

Data Definition

  • Data is the raw material of statistics.
  • Data are figures resulting from counting or taking measurements.
  • Examples include counting patients in a hospital or weighing a patient.

Data Sources

  • Data sources include:
    • Routinely kept records (e.g., medical records, hospital accounting records).
    • External sources (e.g., published reports, data banks, research literature).
    • Surveys (e.g., to collect information on patient transportation).
    • Experiments (e.g., to evaluate different strategies to improve patient compliance).

Variables

  • A variable is a characteristic that takes on different values in different people, places, or things.
    • Examples: heart rate, height, weight, age.

Types of Variables

  • Quantitative Variables: These can be measured in the usual sense.

    • Examples: height of adult males, weights of preschool children, ages of patients in a dental clinic.
    • Discrete: Variables with gaps or interruptions in their values. Example: Number of daily admissions to a hospital, number of decayed teeth per child.
    • Continuous: Variables that can assume any value within an interval. Example: Height, weight, skull circumference.
  • Qualitative Variables: These cannot be measured directly, but can be classified or categorized.

    • Examples: Socio-economic groups, social classes based on income, education.

Populations and Samples

  • Population: The largest collection of values of a random variable for which there's interest. For example, the weights of all children enrolled in a certain elementary school. Populations can be finite or infinite.
  • Sample: A part of a population. For example, the weights of a fraction of the children in the school.

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