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