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Introductory Statistics Vocabulary and Concepts (Chapters 1-3)

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Termini in questo insieme (28)

  • Statistics

    Statistics is the method of collecting, organizing, summarizing data, studying probability, and making inferences based on data analysis.

  • Population

    A population is the entire group of individuals or items that we want information about.

  • Sample

    A sample is a subset of the population used to make inferences about the whole population.

  • Parameter

    A parameter is a numerical summary describing a characteristic of a population.

  • Statistic

    A statistic is a numerical summary describing a characteristic of a sample.

  • Scales of Measurement

    Four scales: nominal, ordinal, interval, and ratio, each with different properties and implications for analysis.

  • Nominal Scale

    Nominal scale classifies data into distinct categories without any order (e.g., gender, colors).

  • Ordinal Scale

    Ordinal scale classifies data with a meaningful order but without consistent differences between ranks (e.g., rankings).

  • Interval Scale

    Interval scale has ordered categories with equal intervals but no true zero point (e.g., temperature in Celsius).

  • Ratio Scale

    Ratio scale has all properties of interval scale and a true zero point, allowing for meaningful ratios (e.g., weight, height).

  • Measure of Central Tendency

    Measures that describe the center of a data set: mean, median, and mode.

  • Mean

    The mean is the arithmetic average of data values, calculated by summing all values and dividing by the number of values.

  • Median

    The median is the middle value when data are ordered from smallest to largest.

  • Mode

    The mode is the most frequently occurring value in a data set.

  • Measure of Variation

    Measures that describe the spread or dispersion of data: range, variance, and standard deviation.

  • Range

    The range is the difference between the maximum and minimum data values.

  • Variance

    Variance measures the average squared deviation of each data point from the mean.

  • Standard Deviation

    The standard deviation is the square root of the variance, representing average distance from the mean.

  • Sample Space

    The sample space is the set of all possible outcomes in a probability experiment.

  • Probability

    Probability quantifies the likelihood of an event occurring, ranging from 0 (impossible) to 1 (certain).

  • Discrete Distribution Mean and Variance

    For a discrete random variable, the mean is the expected value, and the variance measures spread around the mean.

  • Central Limit Theorem

    The Central Limit Theorem states that the sampling distribution of the sample mean approaches a normal distribution as sample size increases.

  • Confidence Interval

    A confidence interval estimates a population parameter with a range of values and a specified confidence level.

  • Hypothesis Testing

    Hypothesis testing is a method to decide if sample data supports a specific claim about a population.

  • Type I Error

    A Type I error occurs when a true null hypothesis is incorrectly rejected.

  • Type II Error

    A Type II error occurs when a false null hypothesis is not rejected.

  • P-value

    The p-value measures the probability of observing data as extreme as the sample, assuming the null hypothesis is true.

  • Sample vs Population Distribution

    Sample distribution describes data from a sample; population distribution describes the entire population.