Lecture 1

Statistics

science that deals with methods of collecting, organizing, tabulating, and analyzing data in order to derive meaningful and Valid interpretation

methods of collecting

Questionnaire, surveys, interviews, observations, and forms

methods of organizing

classification, tabular form, and graphical rep

method of presenting

textual, tabular, and graphical

method of analyzing

mean, mod, median, sd, variance

method of interpreting

conclusion and recommendation

Data (datum)

Any record, descriptive account or symbolic representation of any attributes, events or process expressed in measurable form

Data collection method

1. Census

2. Sampling Method

Census

all individuals in a population

Sampling Method

a portion of the population selected to study the characteristics

two types of data sets

populations and sampling

populations

the collection of all outcomes, responses, Measurements, or counts that are of interest.

sample

a subset or part of the population

why drawing a sample is better than a population

1. manageable number

2. reduced cost

3. minimizing error

4. saves time

Parameter

a numerical description of a population characteristic

Statistic

A numerical description of a sample characteristics

branches of statistics

descriptive statistic and inferential statistics

Descriptive Statistics

Focuses on organizing, summarizing, and presenting data in a meaningful way

What techniques are used in Descriptive Statistics

Calculating measures of central tendency( mean, mod, median ) and dispersion ( Variance and standard deviation)

how to describe data in Descriptive Statistics

Graphical representation like histograms, bar charts and scatter plots

Inferential statistics

Draw conclusion about population based on sample data

what techniques are used in inferential statistics

Hypothesis testing, Confidence interval estimation, and regression analysis

type of data

Qualitative and Quantitative data

Qualitative Data

consist of attributes, labels, or nonnumerical entries

Quantitative Data

Numerical measurements

nominal level of measurements

used to categorized using names, labels, or qualities. can only be qualitative.

ordinal level of measurements

arranged in order or ranked but the difference between data entries are not meaningful. can be qualitative and quantitative

interval level of measurements

can be ordered but the differences have to be meaningful with no inherent zero. this can only be quantitative

ratio level of measurements

can be ordered but the differences have to be meaningful with an inherent zero. this can only be quantitative

Inherent Zero

zero that impalies none

frequency distribution

a table that shows classes or intervals of data entries with a count of numbers of entries in each class

frequency

the number of data entries in the class

the number of intervals (k)

given or 5<K<20

The Range

The Max - The Min

the width of the interval (w)

the Range / the number of intervals (always round up)

the class interval

the minimum and maximum values in a data set

lower boundary

Min+(w)

upper boundary

2nd LB -1

the class lower boundary

LB - 0.5

the class upper boundary

UB + 0.5

The MidPoint

sum of the lower and upper boundary divided by 2

relative frequency

the portion or percentage of the data that falls in that class. the frequency / the sample size

percentage frequency

(the relative frequency) x 100

cumulative frequency

the sum of frequency of that class and all previous classes.