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Ashly Burton

Professor John Schweitzer

Math 1040-014

April 1, 2015

Math 1040 Skittles Term Project

The following project will consist of the concepts I have learned in math 1040. I will be

showing my knowledge of, analyzing and organizing data, and drawing conclusions from

confident intervals, and hypothesis tests. The first part consists of my data that I collected from

my own bag of candy, along with the class data as a whole.

Data Collection

Below is the data for the 2.17 ounce-bag that I purchased Number ofred candies

Number of orange candies

Number of yellow candies

Number of green

candies

Number of purple candies

16 12 12 2 9

Below is the class data

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Organizing and Displaying Categorical Data: Colors

The graphs for my data compared to the class as a whole does not reflect what I expected

to see. There is a bigger gap in the number of candies per color in my bag than that of the

classes’ data. The highest color count in the class bag being purple at 21.09% and the lowest

being orange at 19.01%. In my bag the highest color count in my bag was red at 31.37% and the

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lowest being green at 3.92%. Giving my data I would have expected to see about the same in the

class data.

Organizing and Displaying Quantitative Data: Number of Candies per Bag

Summary statistics:Column n Mean Std.

dev.Media

nMin

Max

Q1Q3

Candies Per Bag

2159.619048 2.747293 60 51 64 58 61

This is not a normal distribution, because it is not the bell shape we would look for in a normal distribution. When you look at the box plot it is easier to see the mean number of candies is 60, but it does not reflect what is in my bag or what I expected to see. My bag is on the low end at 51 candies.

Reflection

The difference between categorical and quantitative is that categorical is labels you put to

thing like, hair color, gender, marital status etc… they can be represented by numbers like male

is 1 and female is 2, but the numbers 1 and 2 have no mathematical meaning. However

quantitative data numbers have a mathematical meaning and can be manipulated. With

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categorical data you would want to use a Pie chart or bar chart like a Pareto chart because the

data is easier to read and understand. For quantitative data you would want to use a histogram,

box plot, or statistic summary to show the numbered data in a meaningful way.

Confidence Intervals

A confidence interval is a range of values that is estimated to contain a population

parameter. Its purpose is to see how accurate that estimate is.

Hypothesis Tests

Hypothesis test is a procedure of testing a claim about a property of a population. The

purpose is to reject false null hypothesis

Reflections

The requirements for interval estimates for a population proportion are that it must be a

simple random and conditions for binomial distribution must be satisfied: fix number of trials,

independent, trials are independent, and two out comes; success and failure. In our case we do

not meet the first requirement; our sample is not a simple random sample. However we do meet

the other requirements.

Interval requirements for population mean are again simple random sample which we do

not meet and the population is normally distributed or n>30 and we do not meet these either.

Interval requirements for population standard deviation are simple random sample which

we do not meet and the population must have normal distributed values, which it does not. So

again we do not meet either requirement.

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The requirements for hypothesis tests for a population proportion are that it must be a

simple random sample, normal distributed and n*p is >/= 5 and n*q is >/= 5. With this sample

we know that this is not a simple random and that it is not normally distributed and we do not

meet the n*p >/= 5 either. Because 21*.20=4.2.

Hypothesis tests for a population mean must be normal distributed and n>30. Which we

do not meet either requirement.

Hypothesis tests for a population standard deviation have a strict requirement of a

normally distributed population, which we definitely do not meet.

Because we do not meet a lot of the requirements we can’t we can make positive or good

estimates about the population. The sample needs to be more random and we need to maybe

have a different population such as an estimate about slcc statistics classes and their bags of

skittles.

Part 4 Final Reflections

What I learned from this assignment was very helpful in understanding simple everyday

statistics that you see on a regular basis. The most interesting part of this assignment for was the

confident intervals because of the formula to get the confident intervals to say what you want it

to say.

I know that I will be using the material that I learned in this class in the future, because of

the fact that I am a psychology major. I will be apply to research that I do in my higher

education. I do think this project and this class has helped with my critical thinking process,

which is some I have need to work on.

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This class made me realizes statistics in general is very important in the real-world it is

something thing that average people see and use every day. I do think it is more important to

learn than other mathematical fields.