Chapter 8: Elementary Quantitative Data Analysis Flashcards
Quantitative data analysis
Statistical techniques used to describe and analyze variation in quantitative measures
Statistic
a numerical description of some feature of a variable or variables in a sample from a larger population
Descriptivie statistics
Statistics used to describe the distribution of and relationship among variables
Inferential statistics
Statistics used to estimate how likely it is that a statistical result based on data from a randoms ample is representative of the population from which the sample is assumed to have beeen selected
Data cleaning
The process of checking data for errors after the data have been entered in a computer file
Central tendency
The most common value (for variables measured at the nominal level) or the value around which cases tend to center (for a quantitative variable
Variability
The extent to which cases are spread out throught he distribution or clustered around just one value
Skewness
The extent to which cases are clustered more at one or the other end of the distribution of a quantitative variable rather than ina symmetric pattern around its center. Skew can be positive (a right skew), witht he number of cases tapering off in the positive direction, or negative (a left skew), with the number of cases tapering off in the negative direction
Three features in describing the shape of the distribution
- Central Tendency
- Variability
- Skewness
Bar chart
A graphic for qualitative variables in which the variable’s distribution is displayed with solid bars separated by spaces
Histogram
A graphic for quantitative variables in which the variable’s distribution is displayed with adjacent bars
Frequency polygon
A graphic for quantitative variables in which a continuous line connects data points representing the variable’s distribution
Frequency distribution
Numerical display showing the number of cases, and usually the percentage of cases (the relative frequencies), corresponding to each value or group of values of a variable
Percentage
The relative frequency, compute by dividing the frequency of cases in a particular category by the total number of cases and multiplying by 100
Base number (N)
The total number of cases in a distribution