Statistics Final Exam Flashcards
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Questions and Answers

What are descriptive statistics?

  • Methods for predicting population behavior
  • Methods for measuring variability
  • Methods for collecting data
  • Methods for summarizing data (correct)

    • What are inferential statistics?

  • Techniques for summarizing data
  • Ways to visualize data
  • Measures of central tendency
  • Methods for making decisions based on data (correct)

    • What are subjects in a study?

    Entities measured in a study

    Define population in statistics.

    <p>All subjects of interest</p> Signup and view all the answers

    What is a sample?

    <p>Subset of the population for whom we have data</p> Signup and view all the answers

    What is a population parameter?

    <p>Numeric summary of a population</p> Signup and view all the answers

    What is a sample statistic?

    <p>Numerical summary of a sample taken from a population</p> Signup and view all the answers

    Randomness means each subject has the same chance of being included in the sample.

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

    Define variability in data.

    <p>The extent to which scores in a data set tend to vary</p> Signup and view all the answers

    Categorical data means each observation belongs to a type or a set.

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

    Quantitative data consists of observations that are numerical.

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

    Discrete data has an infinite set of values.

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

    Provide an example of discrete data.

    <p>Number of pets</p> Signup and view all the answers

    Define continuous data.

    <p>Possible values form an interval, infinite set of values</p> Signup and view all the answers

    Provide an example of continuous data.

    <p>Time, age, weight</p> Signup and view all the answers

    Match the following visual aids with their types:

    <p>Pie chart = Categorical Dot plot = Quantitative Histogram = Quantitative Bar graph = Categorical</p> Signup and view all the answers

    What is a histogram?

    <p>Graph using vertical bars to portray the frequencies of outcomes</p> Signup and view all the answers

    What is an outlier?

    <p>Value falling far from the rest of the data</p> Signup and view all the answers

    What is the mean?

    <p>Sum of values/number of observations, not resistant</p> Signup and view all the answers

    What is the median?

    <p>The midpoint of observations, resistant</p> Signup and view all the answers

    What is the mode?

    <p>Most frequently occurring value, resistant</p> Signup and view all the answers

    A statistic is resistant if outliers have little effect on its values.

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

    Define range in statistics.

    <p>Difference between the minimum value and maximum value</p> Signup and view all the answers

    What is standard deviation?

    <p>How each value differs from the mean</p> Signup and view all the answers

    What does the Empirical Rule state?

    <p>Approximately 68% of observations are within 1 standard deviation of the mean</p> Signup and view all the answers

    Define quartiles.

    <p>Measures of central tendency that divide data into 4 subgroups</p> Signup and view all the answers

    What is a 5 number summary?

    <p>Includes the minimum, first quartile, median, third quartile, and maximum</p> Signup and view all the answers

    Define Interquartile Range.

    <p>Difference between the 75th percentile and 25th percentile scores</p> Signup and view all the answers

    What is a z score?

    <p>Standard score indicating the number of standard deviations from the mean</p> Signup and view all the answers

    What is a response variable?

    <p>A variable whose values are compared across different treatments</p> Signup and view all the answers

    What is an explanatory variable?

    <p>Variable that is manipulated, or the treatment</p> Signup and view all the answers

    Correlation is resistant.

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

    What is regression analysis?

    <p>Make quantitative predictions of one variable from another</p> Signup and view all the answers

    What is a residual?

    <p>Vertical distance between a point and a regression line</p> Signup and view all the answers

    What is extrapolation?

    <p>Calculation of the value of a function outside the range of known values</p> Signup and view all the answers

    Define Simpson's paradox.

    <p>When averages taken across different groups contradict overall averages</p> Signup and view all the answers

    What is the formula for margin of error?

    <p>1/square root of 'n'</p> Signup and view all the answers

    What is a simple random sample?

    <p>Sample size n with equal chance of selection for each set of n elements</p> Signup and view all the answers

    What is sampling bias?

    <p>Exists when a sample is not representative of the population</p> Signup and view all the answers

    What is non-response bias?

    <p>Occurs when certain individuals selected for a survey do not respond</p> Signup and view all the answers

    Study Notes

    Descriptive and Inferential Statistics

    • Descriptive stats summarize data for easy interpretation.
    • Inferential stats involve making conclusions or predictions from data.

    Study Components

    • Subjects are the entities measured in a study.
    • Population encompasses all subjects of interest, while a sample is a subset for which data is collected.

    Statistical Measures

    • Population parameters are numeric summaries of the entire population.
    • Sample statistics represent the numeric summary of a selected sample.

    Randomness and Variability

    • Randomness ensures each population subject has an equal chance of selection for the sample.
    • Variability refers to how much scores differ from one another and from the mean.

    Types of Data

    • Categorical data classifies observations into sets or types.
    • Quantitative data consists of numerical values, categorized as discrete or continuous.

    Data Examples

    • Discrete data examples: number of pets, number of siblings.
    • Continuous data examples: time, age, weight.

    Data Visualization

    • Categorical data visual aids include pie charts and bar graphs.
    • Quantitative visual aides include dot plots, stem-and-leaf plots, and histograms.

    Histogram Definition

    • Histograms use vertical bars to display frequencies of outcomes within intervals.

    Key Statistical Values

    • Outliers are values significantly different from the rest of the data.
    • Mean is calculated as the sum of values divided by the number of observations; it is sensitive to outliers.
    • Median is the middle value, resistant to outlier influence.
    • Mode represents the most frequently occurring value, also resistant to outliers.

    Statistical Resistance

    • Resistant statistics are less affected by outliers, ensuring more stable summaries.
    • Range is the difference between maximum and minimum values.
    • Standard deviation measures how each value differs from the mean.

    Empirical Rule

    • When data follows a normal distribution, approximately 68% of observations fall within one standard deviation of the mean, 95% within two, and 99.7% within three standard deviations.

    Quartiles and Summary Statistics

    • Quartiles divide data into four parts for central tendency measures.
    • The five-number summary includes minimum, first quartile, median, third quartile, and maximum.
    • Interquartile Range (IQR) measures the spread of the middle 50% of data, minimizing the effect of extreme values.

    Z Score

    • A z score represents how many standard deviations a value is from the mean, calculated as (value - mean)/standard deviation.

    Variables in Studies

    • Response variables are the dependent variables measured across treatments.
    • Explanatory variables represent the treatments or manipulations within a study.

    Statistical Relationships

    • Correlation is sensitive to outliers, reflecting that linear relationships may not be consistent across diverse data sets.
    • Regression analysis predicts one variable based on another’s values, supporting correlation.

    Additional Statistical Concepts

    • Residuals measure the vertical distance between observed values and the regression line.
    • Extrapolation involves predicting values outside the known range.
    • Simpson's paradox highlights that averages across groups can contradict overall averages.

    Sampling Considerations

    • The margin of error for sample estimates is calculated as 1/square root of 'n', indicating how well the sample reflects the population.
    • Simple random samples provide every group of 'n' elements equal chances of selection.
    • Sampling bias occurs when the sample does not accurately represent the population, often due to undercoverage.
    • Non-response bias arises when certain individuals do not respond, leading to potential misrepresentation of data.

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    Description

    Prepare for your Statistics final exam with these flashcards covering key concepts like descriptive statistics, inferential statistics, populations, and samples. Each card presents important terms and their definitions to enhance your understanding of statistical methods. Ideal for quick revision and self-testing before the exam.

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