Exercise: Determining the sample size and ANOVA

1) Let us consider the question of how large the sample size should be to obtain an estimate of a population proportion at a specified level of precision. 

In a survey the planning value for the population proportion p is 0.35. 

How large a sample should be taken to provide a 95% confidence interval with a margin of error of 0.05 (Click here to see the Formula).

2) 

A) Use the following data and calculate F-test using ANOVA one-way in excel to show any significant difference between wage and age-groups

B) Is there any significate different between wage of married and non-married population? (use the week-3 code to run a t.test) 

Note: For the age-group use "agecat" and for wage use the "wage"

This week dataset: HMGT400

You can use following codes

*************************************

# Week5-Exercise

# look at the box-plot

boxplot(data$wage ~ data$agecat)

do2.aov <- aov(data$wage ~ data$agecat)

summary (do2.aov)

# use the same analysis for race, you only need to change the agecat with race

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Exercise#5

data <- read.csv("E:/UMUC/Faculty/2017-HMGT-0109-0305/Data/HMGT400.csv", header=T, sep = ',')

#1: See the variables' names

names (data)

#2: Check the histogram for wage and age

# 2a: histogram of age

hist(data$age)

# 2b: histogram of wage

hist(data$wage)

# 2c: histogram of married

hist(data$married)

# as you can see married is the binary variable

# 2d: histogram of school yrs

hist(data$yrschool)

# Model 1:

model1 <- lm(wage ~ age, data=data)

summary(model1)

# Model 2:

model2 <- lm(wage ~ age + married, data=data)

summary(model2)

# Model 3:

model3 <- lm(wage ~ age + married + yrschool, data=data)

summary(model3)

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