Page 152 - Data Science class 11
P. 152
randoMisation
04
Learning Outcome
4.1 Data
4.2 Some Statistical Terms
4.3 Surveys
4.4 Sampling
4.5 Level of Confidence: How sure are you?
4.6 Automatic Data Collection via In-built Sensors
4.7 Structuring Data using XML
4.8 Structure of an XML Document
In the previous chapter, you learnt about how one can use observational studies to collect data. The collected data
is further analysed to derive a conclusion. In this chapter, you will learn about how one can collect data via various
media like surveys, sensory devices, and the Internet. You will also explore a way to increase the accuracy of the results
deduced using a confidence interval.
4.1 Data
As we already know, data is the foundation of data science. All the analyses are based on the type of data. Therefore,
it is a must to understand the different types of data.
4.1.1 types of Data
Let us now learn about the two types of data.
Primary Data
Primary data is a type of data that is collected directly from first-hand sources like interviews, surveys, experiments,
etc. by researchers. Primary data is generally collected from the source—where the data initially originates from. This
data is considered the premier data in research.
The Advantages of Primary Data
• Specific: Primary data is particular to the needs of the researcher during data collection. The researcher is able to
control the type of data that is being collected.
• Controllable: The researcher has complete control over the data gathered through primary research. He can decide
which design, method, and data analysis techniques should be used.
• Accurate: It is more precise than secondary data. The data is free from personal bias and is authentic.
150 Touchpad Data Science-XI

