Sales and analytics intern Interview Questions | Glassdoor

# Sales and analytics intern Interview Questions

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## Top Interview Questions

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### Senior Manager Business Analytics and Enterprise Reporting at Vituity Practice Management was asked...

Mar 19, 2015
 How would I validate the data for integrity of results?1 AnswerCreate quick pivot and then connect to the totals for different reports, using simple logical function in Excel.

Mar 5, 2015

Nov 23, 2016

Mar 5, 2015
 Lets say the population on Facebook clicks ads with a click-through-rate of P. We select a sample of size N and examine the sample's conversion rate, denoted by hat{P}, what is the minimum sample size N such that Probability( ABS(hat{P} - P) < DELTA ) = 95%. In other words (this is my translation), find the minimum sample size N such that our sample estimate hat{P} is within DELTA of the true click through rate P, with 95% confidence.6 AnswersInterpret the question this way: we want to choose an N such that P_hat is an element of [P - delta, P + delta] with probability 95%. First, note that since P_hat is the sum of N Bernoulli trials with some common parameter (by assumption) that we are trying to estimate, we can safely assume P_hat to be normally distributed with mean equal to the true mean (P) and variance equal to (P)(1 - P) / N. Now, we when does a normally distributed random variable fall within delta of it's mean with 95% probability? The answer depends on how big delta is. Since P_hat is normally distributed, we know from our statistics classes that 95% of the time it will fall within 2 standard deviations of its mean. So in other words, we want [P - delta, P + delta] = [P - 2*SE(P_hat), P + 2*SE(P_hat)]. That is, we want delta = SE(P_hat). So what is the SE ("standard error") of P_hat? Well that's just the square root of its (sample) variance, or Sqrt(P_hat * (1 - P_hat) / N). But wait! We haven't run the experiment yet! How can we know what P_hat is? We can either (a) make an educated guess, or (b) take the "worst" possible case and use that to upper bound N. Let's go with option (b): P_hat * (1 - P_hat) is maximized when P_hat is .5, so the product is 0.25. To put it all together: delta = 2 * Sqrt(0.25) / Sqrt(N) = 2 * .5 / Sqrt(N) => N = (1 / delta) ^ 2. So when N is greater than (1 / delta)^2, we can rest assured that P_hat will fall within the acceptable range 95% of the time.Hi, I am not sure I understand your solution. Could anyone explain more?Why is the variance P(1-P) / N. Isn't it NP(1-P), because it is the binomial distribution (sum of Bernoulli trials)?Show More ResponsesUse Chebyshev's inequalityRate has Poisson distribution, not Bernoulli. The mean equals the variance, SE = sqrt(P/N).Doen't the answer imply N >=1?

Mar 5, 2015

Mar 6, 2019

### Marketing Analytics Manager at Hyundai Capital America was asked...

Nov 13, 2015
 what is logistic regression? How to perform variable selection4 AnswersSee answers for Capital One statistician questionsA Measurement of VariablesLogistic regression is a predictive analysis. To explain the relationship between the one dependent variable with another independent variable.Show More ResponsesLogistic regression is a form of predictive modeling where the variable you're predicting has a binary or yes/no answer. Variable selection can be exploratory or confirmatory. In confirmatory analysis, pre-planned models are created and compared for fit and provide relative significance to the model for each value. The best model is the one which balances prosody with explanatory power. In an exploratory analysis, starting from either a model containing all variables or no variables, perform a stepwise model creation to ensure you have good model fit and that the compared models are nested and therefore valid for comparison to one another. Methodology for selecting which variable to include or exclude is often implicit, but this is likely based on the significance (p-value) of each variable, and the correlation between that variable and the outcome variable.

Mar 22, 2012
 Imagine a cube 1x1x1, then imagine that you form a cube of 10x10x10 with all these little cubes of 1x1x1. How many cubes do you have to remove to get rid of the surface of cubes.6 Answers(10*10*10)-(8*8*8)10*10*2 + 10*8*2 + 8*8*22*(10*10)+2*(10*8)+2*(8*8)=488Show More Responsesn^3 - x = (n-2)^3 x = n^3 - (n-2)^3 x = 6n^2 - 12n +8 if n = 10 then x = 488 surface cubes to remove One or more comments have been removed. Please see our Community Guidelines or Terms of Service for more information.

May 28, 2012