Please describe a "real life" example of each term (one sentence in length will suffice). 1. Experimental Study
2. Observational Study
3. Treatment
4. Placebo
5. Nominal Level of Measurement
6. Ordinal Level of Measurement
7. Interval Level of Measurement
8. Ratio Level of Measurement
9. Systematic Sampling
10. Convenience Sampling
11. Stratified Sampling
12. Cluster Sampling
13. Quantitative Data
14. Qualitative Data
15. Discrete Data
16. Continuous Data

1 Experimental Study-In this study detecting the effect on an intervention.In this study investigator artificially manipulate study factors or subjects.

e.g.-Testing of corona Virus Medicine in clinical trail on mouse.

2 Observational Study-Observational studies are ones where we observe the risk factor, diagnostic test treatment or other or other intervention without trying to change.

e.g.-In a study of people to have a control group who are identical to the active group.

3 Treatment- In an experiment the factor is an explanatory variable manipulated by the experimenter. Each factors have two  or more different levels. Combination of factor levels are called treatment.

e.g. The possible effect of vitamin E and Vitamin C on human life. Here vitamin E and vitamin c are two treatments.

e.g. Impact of newspaper and smartphone on daily routine smartphone and newspapers are two treatments.

4 Placebo effect-our mind can be a powerful healing tool when given the chance. The idea that your brain can convince your body a fake treatment is the real thing

e.g.In homeopathic treatment some patient cured without any treatment just using Milk sugar powder.Dr tells him to take this medicine twice a day to control your bp here brain can convince your body a fake treatment is the real thing.

5 Nominal level of measurement-The numbers in the variable are used only to classify the data.  In this level of measurement.

Hair color , eye color.

6 Ordinal level of measurement -e.g.-According to marks students roll number in a class.

7 Interval level of measurement-  The interval level of measurement not only classifies and orders the measurements, but it also specifies that the distances between each interval on the scale are equivalent along the scale from low interval to high interval.

e.g. Giving feedback of to particular biscuit between 1-5

8 Ratio level of measurement- the observations, in addition to having equal intervals, can have a value of zero as well.  The zero in the scale makes this type of measurement.

e.g.-anxiety in a student between the score of 10 and 11, this interval is the same as that of a student who scores between 40 and 41.

9 Systematic Sampling -When first unit is selected rest of the unit selected automatically. e.g.- Every 5th car is checked at check post.at border.

10 Convenience Sampling- Where we include people are easy to reach.It is non probability sampling. e.g (a) Choosing five peoples from class. (b) First five names of patient list.

11 Stratified sampling is a type of sampling method in which the total population is divided into smaller groups or strata to complete the sampling process. The strata is formed based on some common characteristics in the population data. After dividing the population into strata, and randomly selects the sample proportionally.

E.g. In class students are classified according to weight  of the students and the students are selected randomly from weight group

12 Cluster sampling refers to a type of sampling method .With cluster sampling, the researcher divides the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population.

e.g. In a school diving classes as a cluster and selecting classes randomly

13 Quantitative data- As name its clear the data deals with quantity.  

E.g.-No of peoples in a class.

Number of students in the school.

14 Qualitative data- The data deals with quality is called qualitative data.

e.g. Hair color of Indian.

  Top Management students from IIM Ahmedabad (because here IIM ahmedabad is quality)

15 Discrete data- Data in form of number.

Age of students in a particular class  

16 Continuous data- Data in the form of class interval.

Classifying students of class five between weights of student in the interval.20-25 25-30 30-35 35-40 40-45

Step-by-step explanation: