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Questions and Answers
What is the definition of statistics?
What is the definition of statistics?
What is the plural form of a single measurement or observation?
What is the plural form of a single measurement or observation?
Data
Define descriptive statistics.
Define descriptive statistics.
Procedures used to summarize, organize, and make sense of a set of scores or observations.
What is inferential statistics used for?
What is inferential statistics used for?
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What is the population in statistical terms?
What is the population in statistical terms?
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What is a population parameter?
What is a population parameter?
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What is the definition of a sample?
What is the definition of a sample?
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Define a sample statistic.
Define a sample statistic.
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What is science defined as?
What is science defined as?
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What are the elements of control in an experiment?
What are the elements of control in an experiment?
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What is random assignment?
What is random assignment?
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What is the independent variable?
What is the independent variable?
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What is the dependent variable?
What is the dependent variable?
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Define operational definition.
Define operational definition.
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What is a quasi-independent variable?
What is a quasi-independent variable?
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What are scales of measurement?
What are scales of measurement?
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What are nominal scales?
What are nominal scales?
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Define ordinal scales.
Define ordinal scales.
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What are interval scales?
What are interval scales?
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Define true zero.
Define true zero.
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What is a continuous variable?
What is a continuous variable?
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Define discrete variable.
Define discrete variable.
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What is a quantitative variable?
What is a quantitative variable?
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Define qualitative variable.
Define qualitative variable.
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What is frequency in statistics?
What is frequency in statistics?
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What is a frequency distribution?
What is a frequency distribution?
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Define simple frequency distribution.
Define simple frequency distribution.
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What is grouped data?
What is grouped data?
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Define interval.
Define interval.
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What is the real range in a data set?
What is the real range in a data set?
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What is interval width?
What is interval width?
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Define interval boundaries.
Define interval boundaries.
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What is a lower boundary?
What is a lower boundary?
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What is an upper boundary?
What is an upper boundary?
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Define open interval.
Define open interval.
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What are outliers in statistics?
What are outliers in statistics?
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What is cumulative frequency distribution?
What is cumulative frequency distribution?
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Define relative frequency distribution.
Define relative frequency distribution.
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What is a proportion in statistics?
What is a proportion in statistics?
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Define relative percent distribution.
Define relative percent distribution.
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What is cumulative relative frequency distribution?
What is cumulative relative frequency distribution?
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Define cumulative percent distribution.
Define cumulative percent distribution.
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What is a percentile point?
What is a percentile point?
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What is a percentile rank?
What is a percentile rank?
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Define ungrouped data.
Define ungrouped data.
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What is a histogram?
What is a histogram?
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Define frequency polygon.
Define frequency polygon.
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What is an ogive?
What is an ogive?
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Define bar chart.
Define bar chart.
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What is a pie chart?
What is a pie chart?
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Define sector in a pie chart.
Define sector in a pie chart.
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What is central tendency?
What is central tendency?
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Define population size.
Define population size.
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What is sample size?
What is sample size?
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Define mean.
Define mean.
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What is population mean?
What is population mean?
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Define sample mean.
Define sample mean.
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What is a weighted mean?
What is a weighted mean?
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Define median.
Define median.
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What is mode?
What is mode?
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Define normal distribution.
Define normal distribution.
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What is a skewed distribution?
What is a skewed distribution?
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Define positively skewed distribution.
Define positively skewed distribution.
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What is a negatively skewed distribution?
What is a negatively skewed distribution?
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Define modal distribution.
Define modal distribution.
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What is unidimensional or unimodal distribution?
What is unidimensional or unimodal distribution?
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Define bimodal distribution.
Define bimodal distribution.
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What is multimodal distribution?
What is multimodal distribution?
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Define nonmodal distribution.
Define nonmodal distribution.
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What is variability in statistics?
What is variability in statistics?
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Define range.
Define range.
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What is interquartile range (IQR)?
What is interquartile range (IQR)?
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Define semi-interquartile range (SIQR).
Define semi-interquartile range (SIQR).
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What is variance?
What is variance?
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What is population variance?
What is population variance?
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Define deviation.
Define deviation.
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What is sum of squares (SS)?
What is sum of squares (SS)?
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What is sample variance?
What is sample variance?
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Define biased estimator.
Define biased estimator.
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What is an unbiased estimator?
What is an unbiased estimator?
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What are degrees of freedom for sample variance?
What are degrees of freedom for sample variance?
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Define definitional formula for variance.
Define definitional formula for variance.
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What is computational formula for variance?
What is computational formula for variance?
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Define standard deviation.
Define standard deviation.
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What is population standard deviation?
What is population standard deviation?
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What is sample standard deviation?
What is sample standard deviation?
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What does the empirical rule state?
What does the empirical rule state?
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What is Chebyshev's theorem?
What is Chebyshev's theorem?
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Study Notes
Statistics Fundamentals
- Statistics involves summarizing, analyzing, and interpreting a set of numbers or observations.
- Data refers to measurements or observations, with a plural form encompassing multiple scores.
Types of Statistics
- Descriptive Statistics organize and present data through graphical, tabular, or summary forms.
- Inferential Statistics enable generalization from sample observations to a broader population.
Populations and Samples
- A population includes all individuals or items of interest, while a sample is a subset drawn from that population.
- Population parameters are characteristics that describe a whole population, whereas sample statistics do so for a sample.
Research Methodology
- Science is the systematic study of phenomena through observation and interpretation.
- The Scientific Method comprises organized techniques for gathering and processing observable data.
Experimental Design
- Experiments involve controlling conditions to determine cause-and-effect relationships between variables.
- Random assignment helps ensure equal chances for participants to be placed in different study groups.
Variables in Research
- Independent variables are manipulated, while dependent variables are measured and expected to change due to the independent variable.
- Operational definitions detail how variables are observed or measured.
Measurement Scales
- Scales of Measurement set rules for numerical properties, including nominal (categorizing), ordinal (ordering), and interval (equal units without a true zero).
Data Distribution and Display
- Frequency denotes how often scores or categories occur; frequency distributions summarize this occurrence.
- Histograms and frequency polygons visually display data distributions across intervals.
Measures of Central Tendency
- Central Tendency identifies a score that is most descriptive of data: mean (average), median (middle), and mode (most frequent).
- Normal distribution features symmetric distribution of scores around the mean.
Variability in Data
- Variability assesses the spread of scores, calculated using range, interquartile range, variance, and standard deviation.
- The range reflects the difference between the highest and lowest values; interquartile range focuses on the middle 50% of data.
Standard Deviation and Its Importance
- Standard deviation measures how scores deviate from the mean, indicating data spread.
- Empirical Rule states that a normal distribution features 68% of data within one standard deviation, 95% within two, and 99.7% within three.
Estimation in Statistics
- Biased estimators may not accurately reflect population parameters, while unbiased estimators do on average.
- Degrees of Freedom (df) indicate the number of scores in a sample free to vary.
Theorems and Theoretical Applications
- Chebyshev's Theorem provides a percentage of data within any number of standard deviations, applicable regardless of distribution shape.
Summary of Key Terms and Definitions
- Variance quantifies how far data points deviate from the mean.
- Outliers are extreme values significantly different from the rest of the data.
- Cumulative frequency distributions sum frequencies across intervals, providing a comprehensive view of data.
These notes encapsulate the core concepts from Chapters 1-4 of Psychological Statistics, covering definitions, types, and applications in the field.
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Test your knowledge with flashcards covering key concepts from Psychological Statistics Chapters 1-4. This quiz includes essential terms and definitions that are fundamental to understanding statistical analysis in psychology. Perfect for reviewing before the exam!