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Questions and Answers
What is the definition of Statistics?
What is the definition of Statistics?
What does 'Data' refer to?
What does 'Data' refer to?
Pieces of information collected about cases
The Five W's of data are: Who, What, When, Where, _____
The Five W's of data are: Who, What, When, Where, _____
Why
What is meant by 'Categorical Variables'?
What is meant by 'Categorical Variables'?
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What describes 'Quantitative Variables'?
What describes 'Quantitative Variables'?
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Which of the following is a way to summarize the distribution of a categorical variable?
Which of the following is a way to summarize the distribution of a categorical variable?
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What is a 'Contingency Table'?
What is a 'Contingency Table'?
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What do Rows represent in a Contingency Table?
What do Rows represent in a Contingency Table?
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What does a Pie Chart compare?
What does a Pie Chart compare?
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If lines in a graph do not line up and conditional distributions are different, what does this indicate?
If lines in a graph do not line up and conditional distributions are different, what does this indicate?
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What is a Histogram?
What is a Histogram?
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What is the 'Mode' in statistics?
What is the 'Mode' in statistics?
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What does 'Unimodal' refer to?
What does 'Unimodal' refer to?
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The 'Range' of a dataset is the difference between the maximum and minimum values.
The 'Range' of a dataset is the difference between the maximum and minimum values.
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What does the '5 Number Summary' include?
What does the '5 Number Summary' include?
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Study Notes
Statistics
- Involves understanding data and making informed decisions amidst uncertainty.
- Examines variability to guide decision-making processes.
Data
- Comprises pieces of information collected about specific cases, which gain meaning through context.
Five W's of Data
- Who, What, When, Where, Why, and How are crucial aspects to consider in data collection.
Who
- Refers to the subjects or entities (people, places, things) on which data has been gathered.
What
- Represents the information or characteristics collected during the data gathering process.
When
- Details the time frame in which the data collection occurred.
Where
- Indicates the source or origin of the collected data.
Why
- Defines the objectives or purposes behind gathering the data.
How
- Describes the methodologies employed for collecting data.
Variables
- Categorical Variables: Recorded as labels, categorized into distinct groups.
- Quantitative Variables: Measured numerically, representing numeric values with defined units.
Cases and Variables
- Cases: Represented as rows in data tables.
- Variables: Represented as columns in data tables.
Categorical Variable Distribution Summaries
- Frequency table, pie chart, and bar chart are used to summarize categorical variable distributions.
Frequency Table
- Displays the distribution of responses from a survey or study.
Pie Chart
- Visualizes the proportional sizes of various categories, summing to 100%.
Bar Chart
- Illustrates categorical data; measures height to denote differences without requiring a specific order.
Contingency Table
- Examines distribution patterns for two categorical variables, identifying potential relationships.
Counts and Proportions
- Count: Number of observations in a category; when divided by the total, results in a proportion.
Frequency/Relative Frequency Table
- Summarizes the distribution and proportions for a categorical variable with counts.
Mosaic Plot
- Graphically represents conditional distributions from a contingency table, comparable to bar charts.
Association
- Identifies a relationship between variables; closer lines indicate less association, while diverging lines indicate more.
No Association
- Indicates similarity in conditional distributions; lines may not align perfectly yet reflect the absence of association.
Conditional Distribution
- Summarizes one variable's distribution based on specific categories of other variables.
Marginal Distribution
- Represents distributions of individual variables while ignoring other categories.
Quantitative Variable Distribution Summaries
- Shape, center, and variability are key in summarizing quantitative distributions.
Modes
- Mode: The peak(s) observed in a histogram, indicating the most common values.
Distribution Types
- Unimodal: One peak in the distribution.
- Bimodal: Two distinct peaks present.
- Multimodal: More than two peaks observed.
- Uniform: No discernible peaks detected.
- Symmetric: Left and right halves mirror each other in height.
Measures of Dispersion
- Interquartile Range (IQR): Calculated as Q3 minus Q1, measuring variability.
- Range: Difference between the maximum and minimum values in a dataset.
Five Number Summary
- Consists of Minimum, Q1 (first quartile), Median, Q3 (third quartile), and Maximum values.
Sample Mean
- Represents the average of a quantitative variable, essential for central tendency analysis.
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