from turtle import *
import random
if __name__ == ‘__main__’:
number_coins = int(input(‘Enter a number of coins: ‘)) Continue reading
from turtle import *
import random
if __name__ == ‘__main__’:
number_coins = int(input(‘Enter a number of coins: ‘)) Continue reading
Q 1 – ANSWER :
int first, last;
first=1;
last=10;
for (i=first; i<last; i++)
{
} Continue reading
rm(list = ls())
options(warn = -1)
library(readxl)
## Reading the data from excel
Project_2_Data <- read_excel(“Stat 481 Project 2 Data.xls”)
str(Project_2_Data)
## Cleaning and attributing the dtaa
Project_2_Data$courses = as.factor(Project_2_Data$courses)
Project_2_Data$gender = as.factor(Project_2_Data$gender)
levels(Project_2_Data$gender) <- c(“Female”, “Male”)
levels(Project_2_Data$courses) <- c(“Algebra”, “Algebra&Geometry”, “Calculus”)
attach(Project_2_Data)
## Descriptives
library(ggplot2)
library(hrbrthemes)
library(dplyr)
library(tidyr)
library(viridis)
temp = aggregate(score~courses+gender, Project_2_Data, FUN = mean)
qqnorm(score)
ggplot(Project_2_Data, aes(x = score)) + geom_histogram()
summary(Project_2_Data)
p1 <- ggplot(data=Project_2_Data, aes(x=score, fill=courses)) + geom_density(adjust=1.5, alpha=.4) + theme_ipsum()
p2 <- ggplot(data=Project_2_Data, aes(x=score, fill=gender)) + geom_density(adjust=1.5, alpha=.4) + theme_ipsum()
## Model
## Test of normality and other assumptions
ks.test(score, pnorm, mean = mean(score), sd= sd(score))
bartlett.test(score~courses, data = Project_2_Data)
bartlett.test(score~gender, data = Project_2_Data)
## Linear model
model1 = anova(score ~ courses + gender, data = Project_2_Data)
model1
summary(model1)
## Post Hoc
library(DescTools)
PostHocTest(model1, method = “bonferroni”)
PostHocTest(model1, method = “hsd”)
#include <iostream>
#include <string>
using namespace std;
int main()
{
int numItem; Continue reading
Introduction
The article " Unpacking online learning understandings: Online learning self-efficacy and learning satisfaction" issued by four authors: Demei Shen, Moon-Heum Cho, Chia-Lin Tsai and Rose Marra was first accepted by Elsevier Inc for Released on April 8, 2013, and made available on April 15, 2013, for on-line access. Continue reading
creditDF <- read.csv(“Downloads/Credit.csv”)
str(creditDF)
# Q1)
# Exploratory Data Analysis Continue reading
— Query 1 —
SELECT
SUM(number) AS record_count
FROM
`bigquery-public-data.usa_names.usa_1910_2013` Continue reading
---------------CREATE CUSTOMER CREATE TABLE CUSTOMER(CUSTOMERID INT NOT NULL PRIMARY KEY, CUSTOMERFIRST VARCHAR(50) NOT NULL, CUSTOMERLAST VARCHAR(50) NOT NULL , CUSTOMERSTREET VARCHAR(50) NOT NULL , Continue reading
Summary of the Accusation against All Meds Solution Inc., James Darren Dizon Simbulan, Owner and James Darren Dizon Simbulan
Relevant Statutes and Regulations
The accusation falls under the jurisdiction of the California Business and Professions Code (BPC). It is noteworthy that section 118, subdivision (b) states that the suspension, expiration or forfeiture by operation of law of a license shall not hinder the Board of authority or Continue reading
#include <iostream> #include <iomanip> #include "matrix.h" using namespace std; Matrix :: Matrix() { cnt++; row_size = maxRowSize; col_size = maxColSize; for (int r = 0; r < getRowSize(); r++) { for (int c = 0; c < getColumnSize(); c++) { matrix[r][c] = rand() % 10 + 1; Continue reading
{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# Loading the required packages\n", Continue reading
Solution for Statistics - Supply and Demand Task (a) β̂1 = −0.75317 Confidence interval is: ( −0.8050502, −0.7012837 ) (b) For a variable to be valid instrument for log_p , it should be correlated with log_p but uncorrelated with error term (UI ) Continue reading
Solution for Machine Learning using Python for Gradescope Task
#!/usr/bin/env python # coding: utf-8 # Essential Problem 1: # a). Here at least one point is required in each grid, thus the least number of data points are 100 # b). Here the dimension has changed to 3. Thus the least number of data points are 10^3 = 1000. # c). Here the dimension has changed to 3. Thus the least number of data points are 10^(10) Continue reading
Test Question :
Jeb would like to dock his spacecraft with another ship. His problem looks very similar to the
one above, where the goal would be to align the docking clamps of his ship with the hab outside. Continue reading
Physics is an important subject when it comes to academics. Even otherwise, physics is very useful in our day to day life. If you want to become an engineer or a medical student physics is a must. But this essential subject becomes difficult when you are given academic assignments or homework. Continue reading