Classify each of the following as N, nominal, O, ordinal, I/R, interval/ratio data:(1)Pin code of any address (2)Amount of clothes you have (3)Place of your study (4)The last grade you achieved in class (5)Mileage of any car
I/R, O, N, I/R, I/R.
N, I/R, N, O, O.
N, O, N, I/R/ I/R.
I/R, N, O, I/R, N.
N, O, N, I/R/ I/R.
Two variables having r value of 0.01. What things do they suggest?
They are positively co-related.
They show causality.
They are not co-related.
There is a 7% co-relation.
They show causality.
What type of analytics uses statistical and machine learning techniques?
Decision making.
Prescriptive.
Descriptive.
Predictive.
Predictive.
What are the ways to avoid overfitting issues?
By adding a penalty for every data decreasing the complexity.
By testing the model with one-third of the training data itself.
By using the resampling techniques to estimate model accuracy.
All of the above.
All of the above.
Which of the following is not true about unsupervised learning?
It finds clusters of the data.
Finding interesting co-relation and coordinates with the data.
Finding the annotate strings and predicting time series.
Finding low dimensional representations of data.
Finding the annotate strings and predicting time series.
Interviewing all members of a given population is called
A sample.
A gall up pole
Censuses.
Nielsen audit
Censuses.
Which one of the following is the benefit of using simple random sampling?
Informants won’t refuse to participate.
Interviewers can choose respondent freely.
We can calculate the accuracy of the results.
The results are always representative.
We can calculate the accuracy of the results.
What does a dummy variable regression analysis examine?
Relationship between one continuous dependent and one continuous independent variable.
Relationship between one categorical dependent and one continuous independent variable.
Relationship between one continuous dependent and one categorical independent variable.
Relationship between one continuous dependent and one classified variable.
Relationship between one continuous dependent and one categorical independent variable.
What assumptions are made when we use the t-distribution to perform a hypothesis test?
The underline population has a constant variance.
The underline population has a non-symmetrical distribution.
The underline population follows a normal distribution.
All of the above.
The underline population has a constant variance.
Which function used to print all variable names in a data frame df in R?
names()
names(df)
df.names()
names("df")
names(df)
