ISDS 361A Exam #1
ordinal data
-appear categorical but values have rank/order -it is what it is and CANNOT be changed -"hierarchy of data" -ONLY calculations involving ranking process
nominal data
-values are arbitrary $s that represent categories/qualitative -data is categorical in nature, NOT arithmetic -only calculations based on frequencies of occurrence are valid otherwise NO CALCULATIONS
interval data
-values are real #s -ALL calculations valid -quantitative/numerical
confidence + significance = ?
= 1
what is statistics?
a way to get/process info from data data -> statistics -> information
example of population
all 5 million Florida voters university with a total enrollment of 50,000 students
mean
average mark
variable
characteristic of population/sample denoted w/ X, Y, or Z ...
"This poll is considered accurate within 3.4% points, 19 times out of 20."
confidence level is 95% = 19/20 = 0.95 significance level is 5%
parameter
descriptive measure of a population info we need
statistic
descriptive measure of a sample used to make inferences about parameters
inferential statistics
draw conclusions/inferences about characteristics of populations based on sample data
examples of ordinal data
grades "A-F", college course rating system, infant to adult, military, corporate ladder excellent > poor or fair < very good
examples of nominal data
grades= pass/fail gender, marital status, race/ethnicity, religion
population
group of ALL items of interest, very large, infinite
examples of interval data
heights, weights, prices, age, time, income
frequency
how many times it has occurred
median
mark that is 50% above & 50% below
numerical techniques
mean, median used to describe location of data
example of confidence level of 95%
means that estimates based on this form of statistical inference will be correct 95% of the time
example of significance level of 5%
means that in the long run this type of conclusion will be wrong 5% of the time
α = alpha = significance level
measure how frequently conclusion is wrong
typical mark
measure of central location
range
measure of variability = subtract smaller # from biggest # provides little info
descriptive statistics
methods of organizing/summarizing data using: graphical techniques, numerical statistics
data
observed values of a variable in which information is extracted
statistical inference
process of making an estimate/prediction/decision about a population based on sample data what can we INFER about a population's parameters based on a sample's statistics?
1-α = confidence level
proportion of times that estimated procedure is correct
relative frequency
proportion/% frequency/total = ##%
exit polls
random sample of voters who exit polling booth is asked for whom they voted
values
range of possible numerical values for variables
measure of variability
range, variance, standard deviation
example of sample
sample of 765 voters exit polled on election day survey asking 500 students
sample
set of data drawn from population, potentially very large but less than population
inferential statistics
set of methods used to draw conclusions/inferences about characteristics of populations based on data from a sample
statistical applications in business
statistical analysis plays an important role in ALL aspects of business/economics
example of variable
student grades
example of values
student marks on exam (67, 72, 84, 96, 100)
histogram/bar char
uses frequencies
pie chart
uses relative frequencies
