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Introductory Statistics: Chapters 1-3 Key Concepts

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Termini in questo insieme (29)

  • What is a population in statistics?

    A population is the entire group of individuals to be studied.

  • Define a sample in statistics.

    A sample is a subset of the population that is actually studied.

  • What is a parameter versus a statistic?

    A parameter is a numerical summary of a population, while a statistic is a numerical summary based on a sample.

  • Differentiate qualitative and quantitative variables.

    Qualitative variables describe attributes or categories; quantitative variables are numerical measures.

  • What are discrete and continuous quantitative variables?

    Discrete variables have countable values; continuous variables have infinite values along a continuum.

  • Describe the nominal level of data measurement.

    Nominal data are categorical labels with no natural order or math operations (e.g., eye color).

  • What characterizes ordinal data?

    Ordinal data have categories with a natural order but differences cannot be measured (e.g., ratings).

  • Explain interval level of measurement.

    Interval data are ordered numerical values with meaningful differences but an arbitrary zero (e.g., temperature in °C).

  • What defines ratio level data?

    Ratio data have ordered values with meaningful differences and an absolute zero point (e.g., height, salary).

  • What is a simple random sample (SRS)?

    An SRS is a sample where every possible sample of size n has an equal chance of selection.

  • Describe stratified sampling.

    Stratified sampling divides the population into strata and randomly samples from each group.

  • What is systematic sampling?

    Systematic sampling selects every kth individual from the population.

  • Explain cluster sampling.

    Cluster sampling divides the population into clusters and randomly selects entire clusters.

  • What is a convenience sample?

    A convenience sample is drawn from easily accessible individuals and is prone to bias.

  • How is relative frequency calculated?

    Relative frequency = Frequency / Total sum of frequencies; it shows the proportion of observations in a category.

  • What is a histogram used for?

    A histogram displays quantitative data with bars touching to represent continuous class intervals.

  • Define the mean of a dataset.

    The mean is the sum of values divided by the number of values: Sample mean \(\bar{x} = \frac{\Sigma x}{n}\).

  • What is the median?

    The median is the middle value when data are ordered; it is resistant to extreme values.

  • How is sample variance calculated?

    Sample variance \(s^2 = \frac{\Sigma (x - \bar{x})^2}{n-1}\) measures data spread around the mean.

  • What is the formula for the z-score?

    The z-score measures how many standard deviations a value is from the mean: \(z = \frac{x - \bar{x}}{s}\).

  • What is the interquartile range (IQR)?

    IQR = Q3 - Q1; it measures the spread of the middle 50% of data.

  • How do you identify outliers using the 1.5 × IQR rule?

    Outliers are values below Q1 - 1.5×IQR or above Q3 + 1.5×IQR.

  • What is included in the five-number summary?

    The five-number summary includes Minimum, Q1, Median, Q3, and Maximum values.

  • Classify 'number of text messages sent in a day' by variable type and level.

    Quantitative (Discrete) variable at the Ratio level.

  • Classify 'customer satisfaction rating' by variable type and level.

    Qualitative variable at the Ordinal level.

  • Classify 'temperature in degrees Celsius' by variable type and level.

    Quantitative (Continuous) variable at the Interval level.

  • Identify the sampling method: selecting every 15th student.

    Systematic sampling.

  • Identify the sampling method: randomly choosing entire departments and surveying all professors.

    Cluster sampling.

  • Identify the sampling method: selecting equal numbers of men and women from a workforce.

    Stratified sampling.