The standard deviation measures the spread of the data about the mean value. It is useful in comparing sets of datawhich may have the same meaning but a different range. Consider the following data sets in yellow cell of Table 1.Table 1: Two sets of raw dataMean, xX:X:X.X:Standard deviation, sData Set 116| 143015714 2212 23Data Set 230Data Set 338YOUR TASKYour team is required to design and develop a program using C++ programming language. Your C++ program shouldcapable to perform the following tasks based on data in Table 1.Task 1: Lowest valueFind the lowest value of the number entered by the user in task 1. Also, find the occurrences of the lowest value.

Mean of a set can be found using formula , mean = sum of values/ total number of valuesi.e mean =…

Answered: The standard deviation measures the…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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The following table (Training Dataset D) shows the midterm and final exam grades obtained for students in a databas x Midterm exam Final exam 72 84 Plot the data. Do xand y seem to have a linear relationship? b) Find an equation (F(x)) for the prediction of a student's final exam grade based on the student's midterm grade in the course. Predict the final exam grade of a student who received an 86 on the midterm exam. O Find All error measures for the model F(X). * Use MS-Excel or SPSS to find the Model. Compare it with your model you found in (b). 50 63 81 77 74 78 94 90 86 75 59 49 83 79 65 77 33 52 88 74 81 90
Using the ggpubr package and islands data set, PLEASE in R provide the code and steps for the following a. For each sample, conduct a sign test to test the hypothesis that the median size of a landmass in the data set is 100 (this is with the data set units, it would correspond to 1,000,000 sq miles). Use a 95% significance level. Include the results from all 5 tests in your report. You should use the binom.test() function for these tests. b. Do the results of your sign tests differ for the different data subsets? Provide a brief intuitive explanation of your findings. c. For each sample, conduct a sign-rank test the hypothesis that the median size of a landmass in the data set is 100 (this is with the data set units, it would correspond to 1,000,000 sq miles). Use a 95% significance level. Include the results from all 5 tests in your report. d. Do the results of your sign-rank tests differ from the results of the sign test for each of your 5 samples? Provide a brief intuitive…
Upload your own dataset to Rstudio From your dataset: choose a nominal variable and plot its pie chart choose a nominal/ordinal variable and plot its bar chart choose a numerical variable and plot its histogram and its density upload your tidy R codes here
How normalization resolve the problems of the 3 data type anomalies?
Which of the following is not true about standard deviation? a. The larger the standard deviation, the more variable the dataset contains. b. It tells how far each score lies from the mean. c. It is the average amount of variability in a given dataset. d. It is the distance between each score and the mean of the dataset.
Give an example of when you would want to analyze the mean of a dataset.
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Take the first 1000 entries of the training portion of the Scikit-learn 20 Newsgroups dataset (in the original order) as the training set, and set aside the next 100 entries as the test set. Predict whether a post belongs to a political discussion group using a bag-of-words model (category includes 'talk.politics'). Provide the accuracy on the test set, the input shape of the network, and the predictions of the network for the last two entries in the test set as "accuracy on the test set, network input shape, network predictions for the last two entries in the test set as 'politics' or 'non-politics'". Here's what I have so far: from sklearn.datasets import fetch_20newsgroupsfrom sklearn.feature_extraction.text import CountVectorizerimport numpy as npfrom keras.models import Sequentialfrom keras.layers import Dense, Dropoutfrom keras.optimizers import Adam categories = ['talk.politics.guns', 'talk.politics.mideast', 'talk.politics.misc']newsgroups =…
Convert the matrix of observations to mean-deviation form, and construct the sample covariance matrix. [10 13 1 4] 3 063 18 6 6 6 Select one: O A. 30 -3 -15 -12] -3 18 -12 -3 -15 -12 18 -12 -3 9 O B. -30 12 -12 12 -6 0 -12 0-36] 90 -36 36 S = -36 18 0 36 0 108 30 -12 12 60 0 36] C. O D. S= S= S=-12 12 392
using R please show the code needed for each step 1) Initial data overview a. Load the faithful dataset in R b. What are the column headers for this data set? c. How many rows of data are in the data set? 2) Summary stats for the full data set a. Compute all of the following for the duration of the eruptions and the waiting time between the eruptions i. mean ii. population variance iii. population standard deviation iv. population coefficient of variation 3)Sampling a. Create a new data frame that contains 100 samples of size 10 from the eruption duration column of the faithful data set i. You can use the sample() function to create your samples of size 10 ii. You can use the replicate() function to repeat the sampling 100 times iii. You can cast the result as a data frame using data.frame() 4) Analyze the Samples a. Create 3 new empty vectors – these will store the sample mean, sample variance, and sample standard deviation of each of your 100 samples b. For each…
Consider the built-in data frame cars.(a) Determine the number of observations in the dataset as well as the number ofvariables. Also, what are the names of the variables?(b) Find the mean stopping distance for all observations for which the speed was 20miles per hour. (c) Construct a plot relating stopping distance to speed. What kind of relationship do youobserve?
In the ETL process, one important step to process when transforming the data is to work with null, n/a, and zero values in the dataset. If you have a field of quantitative data (e.g., number of years each individual in the table has held a full-time job), what would be the effect of the following? a. Transforming null and n/a values into blanks . b. Transforming null and n/a values into zeroes c. Deleting records that have null and n/a values from your dataset (Hint: Think about the impact on different aggregate functions, such as COUNT and AVERAGE.)

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