Logical Reasoning Problems with Explained Solutions.

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Today's Interview QnAs

Company- Accenture

Role- Data Analyst


1.How would you track down the last line and segment in VBA?

To track down the last column, utilize the underneath lines code in the VBA module:

Sub FindingLastRow()

Faint lastRow As Long

lastRow = ActiveSheet.Cells.SpecialCells(xlLastCell).Row

MsgBox (lastRow)

End Sub

To track down the last section, utilize the beneath lines code in the VBA module:

Sub FindingLastColumn()

Faint lastRow As Long

lastColumn = ActiveSheet.Cells.SpecialCells(xlLastCell).Column

MsgBox (lastColumn)

End Sub


2.How to increase size of pie in tableau?

Creating a pie chart requires atleast one measure and one dimension in row and shelf column. Then you can select a pie chart from either the show me option on the right side of the screen or from the marks card change automatic to pie. Then give some detailing to the pie chart by using a dimension in colour and measure in angle. Option to increase the size also comes under marks card. Click on the size option and then move the slider towards right to increase its size.


3.How to calculate the average in Power BI?

Average can be calculated in two ways-

one is when we add a measure to a visual; by default, it summarizes any measure. When we click on the drop-down for the measure- we can change from Sum to Average. This gives us an average.

The second one is creating a calculated measure for average using the AVERAGE() DAX function.


4.Where is the data stored in Power BI?

The nation or area for the business identity is chosen by the first user in your organization who signs up for Power BI or Microsoft 365. The cloud’s shared identity and access management service, Azure Active Directory (AAD), establishes a tenant in the data center region nearest to the chosen nation or area. AAD is a multi-tenant service, with each enterprise represented in the data center as a separate tenant. The data is saved in the area you choose at sign-up. This region will be the same for all users in your organization, regardless of their location. The chosen region should, ideally, be in the same geographical area as the majority of your consumers.

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Today's Interview QnAs

Company: Etios Limited

Role: Data Scientist


1. How does a Decision Tree handle continuous(numerical) features?
Ans.
Decision Trees handle continuous features by converting these continuous features to a threshold-based boolean feature.
To decide The threshold value, we use the concept of Information Gain, choosing that threshold that maximizes the information gain.


2. What are Loss Function and Cost Functions?
Ans. the loss function is to capture the difference between the actual and predicted values for a single record whereas cost functions aggregate the difference for the entire training dataset.
The Most commonly used loss functions are Mean-squared error and Hinge loss.


3. What is the difference between Python Arrays and lists?
Ans. Arrays in python can only contain elements of same data types i.e., data type of array should be homogeneous. It is a thin wrapper around C language arrays and consumes far less memory than lists.
Lists in python can contain elements of different data types i.e., data type of lists can be heterogeneous. It has the disadvantage of consuming large memory.


4. Write a Program to add two integers >0 without using the plus operator.
Ans.
def add_nums(num1, num2): while num2 != 0: data = num1 & num2 num1 = num1 ^ num2 num2 = data << 1 return num1 print(add_nums(2, 10))


5. Write a query to fetch all employees who also hold the managerial position.
Ans. SELECT E.EmpFname, E.EmpLname, P.EmpPosition FROM EmployeeInfo E INNER JOIN EmployeePosition P ON E.EmpID = P.EmpID AND P.EmpPosition IN ('Manager');


6 . What is root cause analysis? How to identify a cause vs. a correlation? Give examples.
Ans. Root cause analysis: a method of problem-solving used for identifying the root cause(s) of a problem [5]
Correlation measures the relationship between two variables, range from -1 to 1. Causation is when a first event appears to have caused a second event. Causation essentially looks at direct relationships while correlation can look at both direct and indirect relationships.

Example: a higher crime rate is associated with higher sales in ice cream in Canada, aka they are positively correlated. However, this doesn’t mean that one causes another. Instead, it’s because both occur more when it’s warmer outside.
You can test for causation using hypothesis testing or A/B testing.

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Today's Interview QnA

Company- Essar technology

Role- Data Analyst


1.What are the different types of functions generally used in Tableau?

In Tableau, we have a lot of processing and analytical freedom with the virtue of functions available.

With the help of different types of functions, we can perform a lot of analytical operations on the data.

The main categories of Tableau function are:
String function: These functions like ASCII, CHAR, FIND, ISDATE, LOWER, etc, are known as string functions because they work on the string values or characters to manipulate them.

Date function: We use date functions to apply logical as well as arithmetic operations on date values present at the data source.Using the date functions we can manipulate the date values by changing the old values, creating new ones or searching data on the basis of specific dates.

Some commonly used date functions in Tableau are DATEADD, MAKEDATE, ISDATE, MAKETIME, MONTH, MIN/MAX, TODAY, NOW, etc.

Logical function: We use logical functions to perform logical or relational operations on data in Tableau.

Some commonly used logical functions in Tableau are, CASE, IF, IFNULL, ISNULL, ZN, etc.

Aggregate function: We use aggregate functions to apply aggregation on data values in different ways.

Some important aggregation functions used in Tableau are; AVG, ATTR, MAX, MEDIAN, MIN, PERCENTILE, SUM, STDDEV, etc.

User function: We use functions to manage the users registered on Tableau Server or Tableau Online.

Commonly used user functions are, FULLNAME, ISFULLNAME, ISUSERNAME, USERDOMAIN, USERNAME, etc.


2.What do you understand by context filters?

Context filters are used to apply context on the data under analysis.

By applying a context we set a perspective according to which we can see the charts and graphs.

For example, we have sales data of an electronic store and we want to conduct our analysis only for the corporate sector or segment.

To do this, we have to apply a context filter on our Tableau sheet. Once we add the context for the Corporate segment from the Add to context option, all the charts present on the sheet will only show data relevant to the Corporate segment.

In this way, we can apply a context to our analysis in Tableau.


3. How do you add a Note to a cell?

To add a Note, select the cell and right-click on the same. then select the New Note option and type in any note that you wish to. In case you want to delete the Note, follow the same procedure and select the Delete Note option. Notes are indicated by a red triangle at the top-right corner of the cell.


4. What is DAX?

DAX stands for Data Analysis Expressions. It's a collection of functions, operators, and constants used in formulas to calculate and return values. In other words, it helps you create new info from data you already have.


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Today's Interview QnAs
Company - PWC
Role- Data Scientist

1. What is Power of Test?

Power of Test: The Power of the test is defined as the probability of rejecting the null hypothesis when the null hypothesis is false. Since β is the probability of a Type II error, the power of the test is defined as 1- β. In advanced statistics, we compare various types of tests based on their size and power, where the size denotes the actual proportion of rejections when the null is true and the power denotes the actual proportion of rejections when the null is false.


2. Which are the important steps of Data Cleaning?

Different types of data require different types of cleaning, the most important steps of Data Cleaning are:

Data Quality
Removing Duplicate Data (also irrelevant data)
Structural errors
Outliers
Treatment for Missing Data
Data Cleaning is an important step before analysing data, it helps to increase the accuracy of the model. This helps organisations to make an informed decision.

Data Scientists usually spends 80% of their time cleaning data.


3.What is correlation and covariance in statistics?

Correlation is defined as the measure of the relationship between two variables. If two variables are directly proportional to each other, then its positive correlation. If the variables are indirectly proportional to each other, it is known as a negative correlation. Covariance is the measure of how much two random variables vary together.


4.What is the Confusion Matrix?

A confusion matrix is a tabular summary of the number of correct and incorrect predictions made by a classifier. It is used to measure the performance of a classification model. It can be used to evaluate the performance of a classification model through the calculation of performance metrics like accuracy, precision, recall, and F1-score.

For example, in a case of binary classifier, it predicts all data instances of a test dataset as either positive or negative. This produces four outcomes-

True positive(TP) — Correct positive prediction
False-positive(FP) — Incorrect positive prediction
True negative(TN) — Correct negative prediction
False-negative(FN) — Incorrect negative prediction
It helps in calculating various measures including error rate (FP+FN)/(P+N), specificity(TN/N), accuracy(TP+TN)/(P+N), sensitivity (TP/P), and precision( TP/(TP+FP) ).

A confusion matrix is essentially used to evaluate the performance of a machine learning model when the truth values of the experiments are already known and the target class has two or more than two categories of data. It helps in visualisation and evaluation of the results of the statistical process.
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Today's Interview QnAs
Company - The Math Company
Role- ML Engineer

1.Explain Normal Distribution.

Normal Distribution is also called the Gaussian Distribution. It is a type of probability distribution such that most of the values lie near the mean. It has the following characteristics:

-The mean, median, and mode of the distribution coincide

-The distribution has a bell-shaped curve

-The total area under the curve is 1

-Exactly half of the values are to the right of the centre, and the other half to the left of the centre


2. Mention some drawbacks of the Linear Model.

Here a few drawbacks of the linear model:

-The assumption regarding the linearity of the errors

-It is not usable for binary outcomes or count outcome

-It can’t solve certain overfitting problem

-It also assumes that there is no multicollinearity in the data.


3.What are exploding gradients?

Exploding Gradients is the problematic scenario where large error gradients accumulate to result in very large updates to the weights of neural network models in the training stage. In an extreme case, the value of weights can overflow and result in NaN values. Hence the model becomes unstable and is unable to learn from the training data.


4.Explain the Law of Large Numbers.

The ‘Law of Large Numbers’ states that if an experiment is repeated independently a large number of times, the average of the individual results is close to the expected value. It also states that the sample variance and standard deviation also converge towards the expected value.

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