Engineering Data Analysis 2

Statistics

Data (from the word status - state). Collecting, processing, analyzing, summarizing data in order to provide answers to solution to an inquiry. Science that studies data to be able to make a decision.

Inferential

Make conclusions out of the data

Inferential

Make conclusions out of the data

Data

It should be factual. Colletion of facts where you can get facts from survy, observation, etc.

Qualitative Data

(Quality) has no value or magnitude

Quantitative Data

(Quantity) has a value and magnitude

Continuous Value

Infinitely countable things. It can be broken into smaller parts

DIscrete Value

It cannot be broken into smaller parts

Nominal

Lowest level of measurement. It is labels and categories. It has no difference and order

Ordinal

It is a low level of measurement. It has order but no differences.

Interval

A level of measurement with no absolute zero like temperature.

Ratio

Highest level of measurement. It has absolute 0.

Universe

Collection of set of units or entitites from whom we got the data.

Variable

it is a characteristic that is observable or measureable in every unit of the universe.

Population

Set of all possible values of a variable.

Sample

A subgroup of a universe or of a population

Mean

The average value of the data value

Mode

Most frequently occuring data value

Median

middle data value in a round data set

Percentile

Measures of position where m = 100

Quartile

Measures of position where M = 4

Decile

Measures of position where M = 10

Measures of Variation

Spread of data; dispersion

Range

DIfference of the greatest and least

Interquartile Range

The middle half of the data that lies betwen the upper and lower quartile

Standard Deviation

Average amount of variability in dataset

Coefficient of Variation

Ratio betwen standard deviation devided by mean

Normal Distribution

it has bell shaped curve. Mean, median, and mode are equal. Symmetrical about the vertica line through the mean. Maximum area under the curve is 1.

Z score

Tells how many standard deviatin the “x” value is aboe or below the mean.

Probability Density Function

f(x) must be greater or equal to 0, non negative, and should be 1. Probabilty can be find.

Confidence Level

Range of vales so constructed that there is a specified probabilituy of including the true value of a parameter within it. Percentage

Confidence Limits

Two extremes measurements within whihc an observation lies. End points of the confidence interval.

Central Limit Theorem

Irrespective of the shape of the underlying distribution, sample mean, and proportions will approximate normal distribution if the same size is sufficiently large.

Variability of the Population

Describes how far apar the data points lie from each other and from the centre of distribution; spead, scatter, dispersion.

Width of Interval

Relative Deviate (z) is the distanec of the value (x) in units of standard deviation

Hypothesis

A statement of expectation or prediction that will be tested by research.

Null Hypothesis (Ho)

A statement in which there is no relationship between two variables. The researcher tries to disprove. Refers to the population parameter, the testing in indirect and implicit.

Alternative Hypothesis

A statement: that is simply the inverse of the null hypothesis. The researcher wants to prove. Indicates sample statistics, whereon, the testing is direct and explicit.

One-Tailed Method

Hypothesis testing for inequalities

Two-tailed Method

Hypothesis testing for equalities

Type 1 error

False Positive. Rejection of Ho when it is factually true

Type 2 error

False negative. Unable to reject Ho when it is factually false hypothesis due to lack of evidence.