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In situations when linearity is absent, how does linear regression function
When the data is not linear, linear regression works poorly because it presupposes a linear connection between the dependent and independent variables. This leads to biassed and erroneous forecasts....
Describe and Discuss correlation and regression
Correlation evaluates the degree and direction of a linear relationship between two variables, with values ranging from -1 (perfect negative) to +1 (perfect positive). It is assessed using a...
What is a good or terrible R-squared number when performing linear regression?
A high R-squared score in linear regression shows that the model and data are well-fitted. An R-squared value greater than 0.7 is regarded good, indicating that the model explains 70% or more of the...
Could you give any examples of skewed data sets in real life?
Income Distribution: Income data is frequently right skewed, with a small number of people earning extremely high earnings and the bulk receiving moderate to low incomes.House Prices: Real estate...
Can you give any instances of data sets that have a high mean and a low standard deviation?
Data sets with a high mean and a low standard deviation show that the majority of values are tightly grouped around a high central value. Here are few examples:Test Scores in a Well-Prepared Class:...
What is the distinction between PROC SQL and the other SAS procedures?
PROC SQL is a powerful SAS process that allows users to alter and query data using SQL (Structured Query Language). Unlike other SAS procedures, which are generally used for statistical analysis and...
What is log correlation, and why does it matter?
Log correlation is the process of analysing log data from several sources to detect patterns, correlations, and anomalies. It entails comparing events and actions across many logs to acquire...
What is the projected market condition for a data analyst starting out in 2026? What will be the average salary?
Predicting the precise market position for data analysts as newcomers in 2026 is difficult since it is dependent on a variety of factors such as economic conditions, technical improvements, and...
How can I clean time series data?
Cleaning time series data requires multiple stages. First, identify and manage missing values by either imputing or deleting them. Then, look for and address outliers that might bias the analysis....
What is the definition of SPSS?
The acronym SPSS stands for Statistical Package for the Social Sciences. It is a statistical analysis software programme used in a variety of domains such as social sciences, psychology, and market...
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