#dav
- Justify which of the following series are stationary?
- Suppose everyone who visits a retail website gets one promotional offer or no promotion at all. For analyzing whether making a promotional offer makes a difference in visitor behavior on a retail website, you can use a hypothesis test,... 1
- Describe how logistic regression can be used as a classifier. Logistic regression is one of the most popular Machine Learning algorithms, which comes under the Supervised Learning technique. It is used... 1
- List and explain methods that can be used for sentiment analysis. Sentiment analysis is the process of identifying and extracting subjective information from text, such as opinions and emotions. There are s... 1
- Why use autocorrelation instead of autocovariance when examining stationary time series? Autocorrelation and autocovariance are one of the most critical metrics in financial time series econometrics. Both functions are based on c... 2
- What is an analytic sandbox, and why is it important ? An analytical sandbox is a testing environment that is used by data analysts and data scientists to experiment with data and explore various... 1
- Explain Box-Jenkins intervention analysis. Box-Jenkins Methodology PHASE I : Identification and Preparation Data Preparation Differencing the data to achieve stationary series Transfo... 2
- Fit a regression equation to estimate β0 ,β1 and β2 Fit a regression equation to estimate β0 ,β1 and β2 to the following data of a transport company on the weights of 6 shipments, the distance... 3
- estimate the yield when the rainfall is 29 cm and the rainfall when the yield is 600 kg. From the following results, obtain two regression equations and estimate the yield when the rainfall is 29 cm and the rainfall when the yiel... 1
- b. Find two lines of regression from the following data Steps: assume mean dx=x-(assumed mean of x), dy= y – (assumed mean of y) prepare an table and calculate summations of x, y, dx, dy, dx², dy²... 2
- The regression lines of a sample are x +6y=6 and 3x+2y=10 Given data : regression Lines : x +6y=6 __(1) and 3x+2y=10 __(2) To Find : (i) sample means x and y = ? (ii) coefficient of correlation betw... 2
- a) Evaluating the Residuals in Linear regression. A residual is the difference between an observed value and a predicted value in regression analysis. Residual = Observed value – Predicted v... 1
- Explain with suitable example how the Term Frequency Term Frequency-Inverse Document Frequency (TF-IDF) is a statistical measure used in information retrieval and text mining to evaluate the im... 1
- Explain in detail how dirty data can be detected Dirty data refers to inaccurate, incomplete, inconsistent, or duplicate data within a dataset. It can arise from various sources such as hum... 1
- What is regression? What is simple linear regression? Regression analysis is a statistical method used to examine the relationship between one or more independent variables (predictors) and a de... 1
- Difference between Pandas and NumPy. Aspect Pandas NumPy Purpose Data manipulation and analysis Mathematical operations and numerical computing Data Structures Provides DataFram... 1
- DAV previous year question paper solutions? We are trying to publish all question paper solutions for dav we have added it in doubtly.in /category/question-paper-solution/ Previous Yea... 1
- Important questions in Data analysis and visualisation to pass and get good score in finals Ye pdf mila mujhe , PDF Link Download from here https://cdn.jsdelivr.net/gh/YashSarang/B.E-Mumbai-University-Third-Year-AI-CMPN-IT@main/AI-S... 1
- Difference between text mining and text analytics Feature Text Mining Text Analytics Definition Extracting insights from unstructured text using statistical and ML techniques. Analyzing text... 1
- Create a data frame of 10 students’ names, subject and marks. # Create data frame of students' information students <- data.frame( Name = c("John", "Emily", "Michael", "Sophia", "Daniel", "Olivia", "Wil... 1
- What are the steps for text analysis? The steps for text analysis involve several stages to extract meaningful information from unstructured text data. Here’s an explanation of e... 1
- Why and how do we tokenize a text? Why Tokenize Text? Tokenization is a crucial preprocessing step in natural language processing (NLP) that involves splitting text into small... 1
- Explain different types of data visualizations in R programming language In R programming language, there are various types of data visualizations that can be created using different packages such as ggplot2, plot... 1
- Enlist and explain the seven practice areas of text analytics. The Seven Practice Areas of Text Analytics Search and Information Retrieval (IR): This practice area focuses on developing techniques to eff... 1