Statistics
a collection of methods for planning studies and experiments
2 types of statistics
descriptive statistics and inferential statistics
Descriptive statistics
involves collecting, organizing, summarizing, and presenting data with charts, graphs, and tables.
(information is presented in terms of graphs, charts and tables but NO CONCLUSION IS EVER MADE)
Inferential statistics
procedures that are used to draw conclusions, make decisions or predictions about a population based on a sample.
(statistical evidence is presented and A CONCLUSION IS MADE)
What is the difference between descriptive and inferential statistics?
no conclusion is ever made with descriptive and a conclusion is made with inferential.
Census
is the collection of data from every member of a population
Population is the total set of
items.
A sample of is a subset of that
population
There are problems with taking a census:
it can be difficult to complete a census
Random selection
sample data must be collected in an appropriate way
if sample data are not collected in an appropriate way, the data may be
so completely useless that no amount of statistical torturing can salvage them
Sampling bias
non-response and voluntary response, convenience sample
non-repsonse
if only a small fraction of the randomly sampled people choose to respond to a survey, the sample may no longer be representative of the population
voluntary response
occurs when the sample consists of people who volunteer to respond because they have strong opinions on the issue. (such a sample will also not be representative of the population)
convenience sample
individuals who are easily accessible are more likely to be included in the sample
Types of Data
Quantitative and qualitative
Quantitative Data
numbers representing counts or measurements
qualitative data
categorical data (non numeric)
Quantitative data can further be described by distinguishing between
discrete and continuous types
Discrete
finite number of values, data variables that can be counted (the number of students in the room. no fractions, no decimals, WHOLE NUMBERS.)
Continuous
data obtained through measuring. (correspongs to a continous scale with no gaps, interruptions or jumps. Temp, weight, time, distance)
is shoe size discrete or continuous?
discrete
is the length of your foot discrete or continuous?
continuous
is dress size discrete or continuous?
discrete
Shoe size is an exception for discrete or continuous?
discrete
What are examples of continuous data?
temperature, weight
Levels of Measurement
Nominal, ordinal, interval, ratio
Nominal
data that consists of names, labels, or categories. Data can not be arranged in any order. (colors, survey responses)
Ordinal
data that can be arranged in an order but the difference in values is meaningless (can not subtract the values, course grades, size of drinks)
Interval
data at the ordinal level but the difference between the values is meaningful. Data at this level does not have a natural starting point of zero (where none of the quantity is present, body temperature, years)
Ratio
data in the interval level that has a natural starting point at zero (where zero indicates that none of the quantity is present, the cost of a textbook, distance traveled)
Nominal is
qualitative data
Ordinal is
qualitative data
Interval is
quantitative data