Statistics Random Data And Numerical Data
This Statistics chapter is about random data and numerical data.
statistics
a branch of mathematics dealing with the collection, analysis, interpretation and presentation of masses of numerical data
descriptive statistics
organizes, presents, summarizes: graphically, numerically, pictorially..convenient and informative, simplifies comparisons
Inferential
estimates, predicts, decides, draw conclusions or inferences, USES SMALLER AMOUNTS OF DATA
population
is the group (individuals,items, measurements) of interest which is usually not easy to access directly
paramater
describes some characteristics of the population. paramaters are usually unknown
sample
a part of the population that we actually examine and for which we collect data. it is smaller (sometimes more accessible) group
statistic
is a number that describes a characteristic of a sample. often, a sample is used to estimate an unknown parameter
statistical inference
the process of making an estimate, prediction, or decision about a population based on a sample
confidence levels
tells the proportion of time that our conclusion will be correct
significance levels
a numerical measure of how often a result will be wrong
a characteristic of a population or sample of interest
interval
nominal
ordinal
interval
real numbers..heights weights prices- quantitative or numerical histograms
nominal
qualitative or categorical. the values of nominal data are categories. ex: single=1 married=2 pie charts and bar graphs
ordinal
values have an order a ranking to them. order is maintained no matter what numeric values are assigned.
bar chart
used to display frequencies
the bar represents each category, height of the bar represents the frequency
the base of the bar is arbitrary
pie chart
shows relative frequencies. the pies represent categories.
histogram stem and leaf and ogive
are used when the data is interval
contingency table
used to describe the relationship between two nominal variables. lists the frequencies of each combination of the values of the two variables. the data can then be summarized in a bar cart graphically
two interval variables related?
scatter diagram or scatterplot
independent variable
predictor, explanatory- stays the same. is labeled x on the horizontal axis
dependent variable
is the outcome or the response and is labeled y on the vertical axis
one nominal and one interval
bar chart is an effective way to summarize this.
time series plot
observations measured at successive points in time.graphed on a line chart. time periods go on the horizontal axis
mean
average. appropriate for describing interval data.
x-bar
mean for a sample
mu
mean for a population
median
appropriate for interval or ordinal data. best for data dealing with extreme values. computed the same for population and sample. (n+1)/2
mode
occurs most frequently. useful for all data mainly for identifying the group with the highest frequency for nominal data
geometric mean
used when the variable is a growth rate of change.
range
largest observation-smallest observation
variance
population- sigma squared
sample s^2
standard deviation
square root of the variance
Cross-sectional data
data that is collected at a certain point in time. starting salaries of mba students.
longitudinal data
is collected over a period of time. weekly starting prices of gold.
prospective
collected from the current point in the future
retrospective or historical
collected on events that have happened in the past.
sampling
the process of selecting a subset of a whole population. cost efficient. and practical. the sample and the target population should be similar to each other.
sampling plan.
a method or procedure for specifying how a sample will be taken from a population.
simple random
stratified random
cluster sampling
simple random
everyone has an equal chance of being selected
stratified random
separating the population into mutually exclusive set. split into groups first and then use random sampling
cluster sample
a simple random sample of groups or clusters. may increase error