Data Analysis Test Questions And Answers Pdf links:
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Posted on 28-Apr-2021
We think the given Big Data Analytics Online Test is useful for all the applicants to prepare for the examinations. Visit our web portal Allindiaexams. Big data management and data mining B. Data warehousing and business intelligence C. Management...
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[FREE] Data Analysis Test Questions And Answers Pdf | free!
Posted on 28-Mar-2021
Recall measures "Of all the actual true samples how many did we classify as true? One day all of a sudden your wife asks -"Darling, do you remember all anniversary surprises from me? This simple question puts your life into danger. To save your...
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Must Read 26 Data Analyst Interview Questions & Answers: Ultimate Guide 2021
Posted on 1-Mar-2021
And, False Negatives are the cases where you wrongly classify events as non-events, a. In medical field, assume you have to give chemo therapy to patients. Your lab tests patients for certain vital information and based on those results they decide to give radiation therapy to a patient. What will happen to him? Assuming Sensitivity is 1 One more example might come from marketing. Now what if they have sent it to false positive cases? Due to shortage of staff they decided to scan passenger being predicted as risk positives by their predictive model. What will happen if a true threat customer is being flagged as non-threat by airport model?
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Data Interpretation Questions
Posted on 16-Apr-2021
Another example can be judicial system. What if Jury or judge decide to make a criminal go free? In the banking industry giving loans is the primary source of making money but at the same time if your repayment rate is not good you will not make any profit, rather you will risk huge losses. In this scenario both the false positives and false negatives become very important to measure.
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Data Analysis And Interpretation Questions For SBI PO PDF Set-2
Posted on 4-Apr-2021
These days we hear many cases of players using steroids during sport competitions Every player has to go through a steroid test before the game starts. A false positive can ruin the career of a Great sportsman and a false negative can make the game unfair. Validation set can be considered as a part of the training set as it is used for parameter selection and to avoid Overfitting of the model being built. On the other hand, test set is used for testing or evaluating the performance of a trained machine leaning model. In simple terms ,the differences can be summarized as- Training Set is to fit the parameters i. Test Set is to assess the performance of the model i. Validation set is to tune the parameters. True events here are the events which were true and model also predicted them as true.
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70 Regression Analysis Interview Questions & Practice Tests
Posted on 12-May-2021
Selection bias implies that the obtained sample does not exactly represent the population that was actually intended to be analyzed. Missing value treatment is one of the primary tasks which a data scientist is supposed to do before starting data analysis. There are multiple methods for missing value treatment. If not done properly, it could potentially result in selection bias. Let see few missing value treatment examples and their impact on selection- Complete Case Treatment: Complete case treatment is when you remove an entire row in data even if one value is missing.
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Top 30 Data Analyst Interview Questions & Answers
Posted on 21-May-2021
You could achieve a selection bias if your values are not missing at random and they have some pattern. Would you remove all those people? Available case analysis: Let say you are trying to calculate a correlation matrix for data so you might remove the missing values from variables that are needed for that particular correlation coefficient. In this case, your values will not be fully correct as they are coming from population sets. Mean Substitution: In this method, missing values are replaced with the mean of other available values. This might make your distribution biased e. Hence, various data management procedures might include selection bias in your data if not chosen correctly. What would you do if you find them in your dataset?
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Aptitude Test Practice
Posted on 18-May-2021
Support Vector Machine Learning Algorithm performs better in the reduced space. It is beneficial to perform dimensionality reduction before fitting an SVM if the number of features is large when compared to the number of observations. Statistical importance of an insight can be accessed using Hypothesis Testing. Tweet: Data Science Interview questions 1 - How would you create a taxonomy to identify key customer trends in unstructured data? Having done this, it is always good to follow an iterative approach by pulling new data samples and improving the model accordingly by validating it for accuracy by soliciting feedback from the stakeholders of the business. This helps ensure that your model is producing actionable results and improving over the time. You can use the analysis of covariance technqiue to find the correlation between a categorical variable and a continuous variable. If yes, why? Outlier values can be identified by using univariate or any other graphical analysis method.
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Top 65 Data Analyst Interview Questions You Must Prepare In 2021
Posted on 20-May-2021
Each decision tree has a subset of features but includes all the observations from the dataset. In this case, the answer will be as the tree will include all the observations from the dataset. It's very much obvious that you would mention accuracy as the answer to this question but since logistic regression is not the same as linear regression it will mislead. You should mention how you will use the confusion matrix to evaluate the performance and the various statistics related to it like Precision, Specificity, Sensitivity, or Recall. To solve this kind of problem, we need to know — Can you tell if the equation given below is linear or not? What will be the output of the following R programming code?
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Big Data Analytics Multiple Choice Questions And Answers
Posted on 17-Mar-2021
How many Pianos are there in Chicago? How often would a Piano require tuning? How much time does it take for each tuning? We need to build these estimates to solve this kind of a problem. For every 20 households there is 1 Piano. Now the question how many pianos are there can be answered. There is no exact answer to this question. It could be once a year or twice a year. You need to approach this question as the interviewer is trying to test your knowledge on whether you take this into consideration or not. Thus a piano tuner works for days in a year. Considering this rate, a piano tuner can tune pianos a year.
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IBPS PO Data Analysis & Interpretation Questions And Answers PDF Download (Mains)
Posted on 19-Mar-2021
Thus, piano tuners are required in Chicago considering the above estimates. There are 25 horses of which you want to find out the three fastest horses. What is the minimal number of races needed to identify the 3 fastest horses of those 25? Divide the 25 horses into 5 groups where each group contains 5 horses. Race between all the 5 groups 5 races will determine the winners of each group. A race between all the winners will determine the winner of the winners and must be the fastest horse.
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Data Interpretation PDF Free Download: + DI PDF With Solution
Posted on 5-May-2021
A final race between the 2nd and 3rd place from the winners group along with the 1st and 2nd place of thee second place group along with the third place horse will determine the second and third fastest horse from the group of The first beaker contains 4 litre of water and the second one contains 5 litres of water. How can you our exactly 7 litres of water into a bucket? Do you think the coin is biased? If a girl is born, they plan for another child. If a boy is born, they stop. Find out the proportion of boys to girls in the city.
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Top 65 Data Analyst Interview Questions And Answers For | Edureka
Posted on 14-Apr-2021
You have to decide whether the data provided in the statements are sufficient to answer the question. Read both the statements and Give answer a if the data in Statement I alone are sufficient to answer the question, while the data in Statement II alone are not sufficient to answer the question, Give answer b if the. Give answer c if the data in Statement I alone or in Statement II alone are sufficient to answer the question. Give answer d if the data in both the Statements I and II are not sufficient to answer the question. Give answer e if the data in both the Statements I and II together are necessary to answer the question. Question: In how many days will five women complete a work? Two women, five boys and three men together complete the work in eight days. Six women complete the same work in sixteen days.
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Data Analyst Interview Questions
Posted on 17-May-2021
Shekhar is six years older than Pravin. Ans: e Question: What is the area of a circle? The radius of the circle is equal to length of a rectangle. The breadth of the rectangle is equal to 22 cms. Ans: d Question: What is the average speed of a car? Average speed of the car is four times average speed of a truck which covers kms in 11 hours. Ans: a Directions next 5 questions : Study the following graph carefully to answer the questions: Question: In the income of company A in the year was?
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100 TOP DATA STRUCTURES And ALGORITHMS Multiple Choice Questions And Answers
Posted on 8-Apr-2021
Rank statistics, percentile, outliers detection Imputation techniques, etc. Mathematical optimization 26 What is time series analysis? Time series analysis can be done in two domains, frequency domain and the time domain. In Time series analysis the output of a particular process can be forecast by analyzing the previous data by the help of various methods like exponential smoothening, log-linear regression method, etc. A correlogram analysis is the common form of spatial analysis in geography. It consists of a series of estimated autocorrelation coefficients calculated for a different spatial relationship. It can be used to construct a correlogram for distance-based data, when the raw data is expressed as distance rather than values at individual points. In computing, a hash table is a map of keys to values.
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Data Interpretation Questions And Answers
Posted on 22-May-2021
It is a data structure used to implement an associative array. It uses a hash function to compute an index into an array of slots, from which desired value can be fetched. How is it avoided? A hash table collision happens when two different keys hash to the same value. Two data cannot be stored in the same slot in array. To avoid hash table collision there are many techniques, here we list out two Separate Chaining: It uses the data structure to store multiple items that hash to the same slot. Open addressing: It searches for other slots using a second function and store item in first empty slot that is found 29 Explain what is imputation? List out different types of imputation techniques? During imputation we replace missing data with substituted values.
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Data Science Interview Questions And Answers For
Posted on 5-Mar-2021
The types of imputation techniques involve are Single Imputation Hot-deck imputation: A missing value is imputed from a randomly selected similar record by the help of punch card Cold deck imputation: It works same as hot deck imputation, but it is more advanced and selects donors from another datasets Mean imputation: It involves replacing missing value with the mean of that variable for all other cases Regression imputation: It involves replacing missing value with the predicted values of a variable based on other variables Stochastic regression: It is same as regression imputation, but it adds the average regression variance to regression imputation Multiple Imputation Unlike single imputation, multiple imputation estimates the values multiple times 30 Which imputation method is more favorable? Although single imputation is widely used, it does not reflect the uncertainty created by missing data at random.
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Data Interpretation Questions With Solutions PDF
Posted on 13-May-2021
So, multiple imputation is more favorable then single imputation in case of data missing at random. N-gram: An n-gram is a contiguous sequence of n items from a given sequence of text or speech. It is a type of probabilistic language model for predicting the next item in such a sequence in the form of a n Criteria for a good data model includes It can be easily consumed Large data changes in a good model should be scalable It should provide predictable performance A good model can adapt to changes in requirements.
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70 Regression Analysis Interview Questions & Practice Tests - Data Analytics
Posted on 6-Apr-2021
Recall measures "Of all the actual true samples how many did we classify as true? One day all of a sudden your wife asks -"Darling, do you remember all anniversary surprises from me? This simple question puts your life into danger. To save your life, you need to Recall all 12 anniversary surprises from your memory. Thus, Recall R is the ratio of number of events you can correctly recall to the number of all correct events. However , you might be wrong in some cases. For instance, you answer 15 times, 10 times the surprises you guess are correct and 5 wrong.
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100+ Data Science Interview Questions You Must Prepare For 2021
Posted on 14-Apr-2021
Precision is the ratio of number of events you can correctly recall to a number of all events you recall combination of wrong and correct recalls. Regularizations in statistics or in the field of machine learning is used to include some extra information in order to solve a problem in a better way. In the example shown above H0 is a hypothesis.
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Download Sample Excel Assessment Test PDF Workbook
Posted on 15-Mar-2021
So in L1 variables are penalized more as compared to L2 which results into sparsity. In other words, errors are squared in L2, so model sees higher error and tries to minimize that squared error. Seasonality makes your time series non-stationary because average value of the variables at different time periods. Differentiating a time series is generally known as the best method of removing seasonality from a time series. Seasonal differencing can be defined as a numerical difference between a particular value and a value with a periodic lag i.
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Data Analysis MCQ Questions And Answers - Letsfindcourse
Posted on 20-Mar-2021
Compare hold-out vs k-fold cross validation vs iterated k-fold cross-validation methods of testing. Before we start, let us understand what are false positives and what are false negatives. False Positives are the cases where you wrongly classified a non-event as an event a. And, False Negatives are the cases where you wrongly classify events as non-events, a. In medical field, assume you have to give chemo therapy to patients. Your lab tests patients for certain vital information and based on those results they decide to give radiation therapy to a patient. What will happen to him? Assuming Sensitivity is 1 One more example might come from marketing. Now what if they have sent it to false positive cases? Due to shortage of staff they decided to scan passenger being predicted as risk positives by their predictive model. What will happen if a true threat customer is being flagged as non-threat by airport model?
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Aptitude Test - FREE Online Practice Aptitude Tests
Posted on 28-May-2021
Another example can be judicial system. What if Jury or judge decide to make a criminal go free? In the banking industry giving loans is the primary source of making money but at the same time if your repayment rate is not good you will not make any profit, rather you will risk huge losses. In this scenario both the false positives and false negatives become very important to measure. These days we hear many cases of players using steroids during sport competitions Every player has to go through a steroid test before the game starts.
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