Podcast
Questions and Answers
What is the primary concern of the field of statistics?
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?
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?
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?
When might a survey be the appropriate source of data?
What type of data arises from counting or measuring?
What type of data arises from counting or measuring?
What is the primary characteristic of a discrete variable?
What is the primary characteristic of a discrete variable?
Which of the following best describes a population in statistical terms?
Which of the following best describes a population in statistical terms?
In which of the following situations would a qualitative variable be appropriate?
In which of the following situations would a qualitative variable be appropriate?
What differentiates continuous variables from discrete variables?
What differentiates continuous variables from discrete variables?
Which of these is an example of a quantitative variable?
Which of these is an example of a quantitative variable?
Flashcards
Biostatistics
Biostatistics
The application of statistical tools and concepts to biological sciences and medicine.
Data
Data
Figures resulting from counting or measurements, the raw material of statistics
Statistics
Statistics
The collection, organization, summarization, analysis, and interpretation of data.
Population
Population
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Sample
Sample
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Variable
Variable
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Quantitative Variable
Quantitative Variable
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Discrete Variable
Discrete Variable
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Continuous Variable
Continuous Variable
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Population
Population
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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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