Collection,Organization,Summarization of Data. e.g Survey,analysis etc.

it is used to describe or characterize data by summarizing them into more understandable terms without losing or distorting much of the information 

Drawing inferecnes about a body of data based on what is colleceted and finalized 

Consists of a set of statistical techniques that provide predictions about population based on information in a sample from that population 

The group to which you will generalize (whoever is doing the study)

A set of observations or scores about which the researcher wishes to draw conclusions

Independent Variable: The one that you manipulate e.g drug (cause). for example u manipulate th drug u want to use to cure blood pressure. 

Dependedent Variable: The outcome, like a blood level, or coronary disease(effect). blood pressure becomes the dependent variable. 

Discrete Variable: Fixed integers like 0,1,2,3,4,5... finite number of values.

Comtinuous Variable: can be divided into fractions. 1.5,2.3,0.5 etc. it can assume an infinite number of values btw 2 points. for example a persons age can be 2years 5months 3days old. 

1) Categorical 

2) Interval scale 

3) Ratio scale

Classify characteristics of the persons, places or objects into categories. Also called qualitative

3 types:

a) Nominal

b) Binary

c) Ordinal 

Means order. from low to high vice versa, small to big etc. some type of order. 

letter grades: A,B,C,D,F

Birth Order: 1st,2nd,3rd

Breast Cancer: stage 1,2,3 or 4

health staus: poor,fair,good,excellent

2 categories 

yes or no 

dead or alive 

infected or not infected 

hospitalized or not hospitalized 

The distance btw these ordered category values are equal because there is some accepted physical unit of measurement 

• The most precise level of measurement
• zero represents absence of any length 

The time it takes for an event to occur, if it occurs at all. it is a hybrid variable meaning that it has a continous part (time) and a binary part (event:yes/no) e.g 

time to death

time to heart attack 

Bar Chart is a categorical variable which is used to show frequency or proportion in each category  

They are quantitative variables. 

They are used to show the distribution (shape,center,range,variation) of quantitative variables. 

• obtained by dividing frequency for that class by total number of observations 

• It gives you the percentage of that observation

• Has predictable behaviour
• Many traits follow a normal distribution in the population 

quantifies whether the shape of the data matches the the normal distirbution 

Kurtosis has no units 

The outliers will affect the average of the mean but wont affect the median

for example the kid that got a 100 on the test is the outlier which affected the average of the whole class. 

Mode

• Very quick and easy to determine 

• gets back to unit of the original data
• average spread around the mean
• standard deviation is affected by extreme rules 

Incidence rate is the rate at which people are developing a disease 

• for example, there are 20 new cases of heart disease per 1000 men per year.  

• The proportion (percentage) of people who have a disease at a given point in time; includes old and new cases
• For example, 10% of men over 70 have heart disease

• Measurement combining the number of persons and their contribution in a study
• It is the sum of individual units of time that the persons in the study population have been exposed or at risk to the conditions of interest. (most frequently used person-time is person-years).

• Probability must sum to 1
• Probability of at least 1 = 1-p(none)
• it means MULTIPLY or means ADD
• If A and B are independent, then: P(A&B) = P(A)*P(B)

1) Theorectical/ classical probability is based on theory 

2) Empirical Probability: based on empirical data