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What are the key differences between statistics and economics, and how do they intersect in the field of data analysis?
Statistics is the study of collecting, analyzing, and interpreting data, while economics focuses on the production, distribution, and consumption of goods and services. In data analysis, statistics is used to analyze and interpret economic data to make informed decisions. Economics provides the context and real-world applications for statistical analysis, helping to understand and predict economic trends and behaviors.
What are the key differences between econometrics and statistics, and how do they impact the analysis of economic data?
Econometrics focuses on applying statistical methods to economic data to test economic theories and make forecasts, while statistics is a broader field that deals with collecting, analyzing, and interpreting data in various disciplines. The key difference lies in their specific application and purpose. In the analysis of economic data, econometrics helps economists understand and quantify relationships between variables, while statistics provides tools for summarizing and interpreting data more generally. Econometrics allows for more precise modeling of economic phenomena, while statistics offers a broader range of techniques for data analysis.
Explain about Nature and scope of business statistics?
all fied is collect of data then needs of sytistics
What are relationship between econometrics and statistics?
Econometrics is basically applied statistics. The theory you learn in statistics can be used to answer questions posed in the field of economics. Because this application is mathematical, it allows economists to perform research using economic data in an empirical, scientific, and rigorous manner.
Why are graphs useful?
Graphs are useful in various ways. They are commonly used in statistics to represent data which can be easily interpreted by other users.
What are the differences between Homogeneous and non homogeneous data structures?
in homogeneous data structure all the elements of same data types known as homogeneous data structure. example:- array while there can b any type of data in non homogeneous data structure. example:- list
What is a homogeneous data structure and why is this a weakness for RDBMS?
in homogeneous data structure all the elements of same data types known as homogeneous data structure. example:- array
What is type of data connection?
data is collection of data nd is many type linear non linear homogeneous non homogeneous etc
What is homogeneous data structure?
collection of dissimilar type of data is called non homogeneous data structure as for example structure .
3 ways of presenting data in statistics?
ways of presenting data in statistics
What is non homogeneous material?
collection of dissimilar type of data is called non homogeneous data structure as for example structure .
What are cases in statistics?
In statistics, cases are comprised of the data that is being studies. The cases in statistics can be updated frequently as the data changes.
The classification and collection of data that are in the form of numbers is called?
Statistics
What are descriptive statistics and inferential statistics?
Descriptive statistics is a summary of data. Inferential statistics try to reach conclusion that extend beyond the immediate data alone.
Why it is said all statistics are data but all data are not statistics?
All statistics are data because all statistics are formed of numbers and numbers are a type of data (numrical). But not all data is statistics because not all data is numbers, it can also be words, pictures etc. It's like saying all apples are fruit but all fruit are not apples.
Which data structure can't store the homogeneous data elements?
arrays
What data structure is used to store homogeneous data item?
array
