Statistics: Science of conducting studies to collect and organize

Statistics: Science of conducting studies to collect and organize/summarize/analyze and draw
conclusions about data
There are multiple parts of statistics
Variable: characteristic that can assume different values usually independent/dependent variable
independent is the your experimental product etc., dependent depends on the independent
Data: Values that the variables can assume measurements or observations for the variable
Facts and statistics collected together
each data point is in a data set
Random variables – variables that values are determined by chance
Data set- collection of data values
Data value/Datum- value in a data set usually represented in a data table
Descriptive stats- collection/organization/summarization/presentation of the data
Specific and describes the situation
Inferential stats –consists of generalizing from samples to populations performing estimations and
hypothesis test, determining relationships between variable and making predictions
Draws a conclusion from a smaller number to a larger group
Probability – the chance of an event occurring
can be measure in several ways percentages/ fractions/ratios
used for inferential stats
likelihood of something happening
different types of probability various forms of gambling etc.
Population- Often represented with the variable N consists of all subjects that are being studies
can be human or otherwise
Sample – a group of subjects from the population/ a part of the population
when they are picked they should have the same or similar characteristics
same percentages of the overall population
used in inferential statistics
Hypothesis testing: decision making process for evaluation claims about a population
also based on information that came from samples
used in inferential statistics
Qualitative stats: variable that can be placed in to categories according to some characteristic or
attribute (gender etc.)
Quantitative variables: variable that is based on numbers that need to be ordered or ranged
opposite of qualitative
Discrete variable: they assume values that can be counted
generally whole number items (number of chairs in the room)
Continuous variables: can assume an infinite number of values they are obtained by measuring and
often contain fractions and decimals
Nominal level of measurement: classifies data in mutually exclusive categories in which no order or
ranking in imposed
non overlapping
Ordinal level of measurement: categorizing data that can be ranking with differences between the ranks
Interval level of measurement: ranking of data where precise levels of differences do exist, there is no
meaning for zero
Ratio level of measurement: possess all characteristics of interval but contains zero