Publications by University Solutions Hub

Week 9 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 9 solution (Visual Analytics). Week 9: working with models Using the gapminder data, create a plot comparing log(gdp PerCa with Life Exp and show three different smoothers in three different colors with a legend showing each smoother type. In a paragraph compare and contrast the smoother ...

1779 sym

Week 10 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 10 solution (Visual Analytics). Week 10: working with models2 load the broom library use tidy() on the out dataframe to produce a new dataframe of component level information. Store the result in out_comp. round all the columns to two decimal places using round_df(). Produce a flipped sca...

1294 sym

Week 11 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 11 solution (Visual Analytics). Week 11: working with models3 Take a slice of the gapminder data showing only 1977 create a linear model of with lifeexp being the target of the log of gdpPercap. Save it in a variable called fit and show the summary. Group the entire data set by continent a...

1750 sym

Week 12 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 12 solution (Visual Analytics). Week 12: working with models4 load the margins library create a new column called called polviews_m to use Moderate as a reference category using relevel on the polviews column of the gss_sm data. use glm() to create a model called out_bo using logistic reg...

1366 sym

Week 14 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 14 solution (Visual Analytics). Week 14: Refinements in ggplot look at the first six rows of the asasec dataset plot members v revenue for 2014 in a scatterplot with a confidence interval switch from loess to ols and add the Journal variable show the first six rows of studebt create a face...

909 sym

Week 13 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 13 solution (Visual Analytics). Week 13: covid 19 Find a graph of covid 19 disease or economic data in a newspaper, journal, or website and recreate it. Find a map of covid 19 disease or economic data in a newspaper, journal, or website and recreate it. Note: Only for knowledge gain and ...

601 sym

Week 15 VA

19.04.2023

University Solutions Hub provides Visual Analytics Week 15 solution (Visual Analytics). Week 15: Mapping. pipe the election data through the select() function to pick out the following columns - state, total_vote, r_points, pct_trump, party, census. Pipe that through sample() to see the first five rows. Create a state level dotplot of election...

1807 sym

Week 1 ML

19.04.2023

University Solutions Hub provides Machine Learning Week 1 solution (Machine Learning). Week 1: Introduction to ML You are expected to be able to program in R prior to taking this class. Use Titanic dataset and perform EDA on various columns. Without using any modeling algorithms, and only using basic methods such as frequency distribution, des...

836 sym

Week 2 ML

19.04.2023

University Solutions Hub provides Machine Learning Week 2 solution (Machine Learning). Week 2: Fundamentals of Machine Learning and Introduction to Cases Studies Part One Write a fully executed R-Markdown program and submit a pdf / word or html file. The program should merge / join the data files given to you as part of the Santander Bank Case...

1049 sym

Week 4 VA

10.04.2023

University Solutions Hub provides Visual Analytics Week 4 solution (Visual Analytics). Week 4: Plotting Show meta data from the mpg dataframe using summary(). Show metadata from the gapminder dataframe assign ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp) to the variable ā€˜pā€™ find the structure of the p object. add geom.p...

1498 sym