Skip to main content
Indietro

Introductory Statistics: Chapter 1 and 2 Key Concepts

I pulsanti di controllo sono stati cambiati in modalità "navigazione".
1/26

Termini in questo insieme (26)

  • What is Statistics?

    Statistics is the science of collecting, analyzing, interpreting, presenting, and organizing data.

  • Define Parameter.

    A parameter is a numerical value that describes a characteristic of a population.

  • Define Statistic.

    A statistic is a numerical value that describes a characteristic of a sample.

  • What are Variables in statistics?

    Variables are characteristics or attributes that can assume different values.

  • What are the Levels of Measurement?

    The levels are Nominal, Ordinal, Interval, and Ratio, which classify data based on their nature and the mathematical operations allowed.

  • What is a Lurking Variable?

    A lurking variable is an unobserved variable that influences the relationship between the studied variables.

  • Explain Cluster Sampling.

    Cluster sampling divides the population into clusters, then randomly selects entire clusters for the sample.

  • Explain Stratified Sampling.

    Stratified sampling divides the population into strata, then randomly samples from each stratum proportionally.

  • What is Bias in sampling?

    Bias is a systematic error that causes the sample to misrepresent the population.

  • What does Skew mean in a distribution?

    Skew describes the asymmetry of a distribution; it can be left (negative) or right (positive) skewed.

  • Difference between Statistic and Parameter?

    A parameter describes a population, while a statistic describes a sample.

  • How to identify if a variable is Discrete or Continuous?

    Discrete variables have countable values; continuous variables can take any value within a range.

  • Difference between Qualitative and Quantitative variables?

    Qualitative variables describe categories; quantitative variables represent numerical values.

  • Explain Nominal level of measurement.

    Nominal data are categories without order or ranking.

  • Explain Ordinal level of measurement.

    Ordinal data have categories with a meaningful order but no consistent difference between ranks.

  • Explain Interval level of measurement.

    Interval data have ordered categories with equal intervals but no true zero point.

  • Explain Ratio level of measurement.

    Ratio data have ordered categories, equal intervals, and a true zero point.

  • Difference between an Experiment and an Observation?

    An experiment involves manipulating variables; an observation involves measuring without intervention.

  • How to calculate k in a systematic sample?

    k = population size ÷ sample size; it determines the interval for selecting samples.

  • What is Response Bias?

    Response bias occurs when participants answer questions untruthfully or inaccurately.

  • What is Nonresponse Bias?

    Nonresponse bias occurs when some selected individuals do not respond, skewing results.

  • What is Sampling Bias?

    Sampling bias happens when the sample is not representative of the population.

  • How to create a Frequency Distribution?

    List data values and count how often each occurs.

  • What is a Relative Frequency Distribution?

    A distribution showing the proportion or percentage of each data value relative to the total.

  • What is a Discrete Frequency Histogram?

    A bar graph representing frequencies of discrete data values.

  • How to interpret a Time-Series Graph?

    Analyze data points plotted over time to identify trends and percent changes.