IT-223 - Assignment #1 Quintin Gray
Submit your assignment to the D2L Dropbox.
And again, please remember not to wait until the last minute in case you run into
glitches with D2L or your own computer.
All questions in this assignment should be saved into
Samir Shallwani
Module 7
1) If the p-value =0.20, which is the best conclusion?
d)
Data do not provide enough evidence to reject H0
If p-value is LARGER than 0.05, the null hypothesis CANNOT BE REJECTED. The test
is not significant.
2) A study carried out
Samir Shallwani
10/20/11
IT 223
Part 1
Trial
1
2
3
4
Total
Number of displayed
symbols
25
25
25
25
100
Number of correct
guesses
10
3
9
6
28
Percentage of
correct guesses
40%
9%
36%
24%
28%
Without any trials, there would be a 1/5, 20% chance of guessing
The article Curve of Forgetting informs readers about how information learned in a one hour
lecture can either be stored in our memory or easily disposed of by the brain. The article includes a
graph that shows how much people forget over time. By the end
R^2-Coefficient of Determination. Square of correlation coefficient. R^2 tells you to what degree X
affects Y.
R = -1
R^2 = 1 or 100% Changes in X explain 100% of the variations in y. Y can be entirely predicted for a
given X.
R = 0.87
R^2= 0.76
Change in
Question 1:
1) Using the Z-Table
The Z-Score is 1.48
1.48 = (x-470)/85
X = 595.8
2) Using the Z-Table
The Z Score is -0.25
-0.25 = (x-470)/85
X = 448.75
3) Z-Score for X = 580
1.29
Z-Score for X = 380
-1.06
Corresponding Areas
(1.29) = 90.15%
(-1.06) = 14
Yamini Bangarusamy
ASSIGNMENT #4
1.
a.
b. The correlation coefficient is 0.803.
c. The scatterplot is linear, has a positive direction, and the strength of the scatterplot is
strong.
d. R2 = 0.645.
Change in x describes 64.5% of the change in y. 35.5% of
Question 1:
1) Using the Z-Table
The Z-Score is 1.48
1.48 = (x-470)/85
X = 595.8
2) Using the Z-Table
The Z Score is -0.25
-0.25 = (x-470)/85
X = 448.75
3) Z-Score for X = 580
1.29
Z-Score for X = 380
-1.06
Corresponding Areas
(1.29) = 90.15%
(-1.06) = 14
2.
The Mean is 196.58 seconds.
The SD is 342.022 seconds.
12 calls lasted longer than 5 minutes
Question 2:
1. Score of 24 has a Z-Score of +1. Percentile is area under the curve up to one standard deviation
above the mean.
68% (Area under the curve betwe
Question 1:
1) Using the Z-Table
The Z-Score is 1.48
1.48 = (x-470)/85
X = 595.8
2) Using the Z-Table
The Z Score is -0.25
-0.25 = (x-470)/85
X = 448.75
3) Z-Score for X = 580
1.29
Z-Score for X = 380
-1.06
Corresponding Areas
(1.29) = 90.15%
(-1.06) = 14
Data Analysis EDA Practice Problems
DO NOT SUBMIT
Answers to ALL odd numbered problems are in the text addendum
th
Problems are based on 8 edition numbering.
Students can find problems with similar wording or numbering in prior editions
1.127 Find proport
IT-223 Assignment # 7
1.
a.
Distribution of the Sample Means: N(7.62, 0.1170)
Mean is the same as the population Mean. The Standard Error is the
SD/SQRT(Sample Size)
Mean = 7.62
Standard Error = 1.85/SQRT(250)
b. Distance from Mean = 6.0-7.62 = -1.62
C
How to Succeed in IT223
DO
All the quizzes
All the assignments
Come to all the
classes
Engage, participate!
DO NOT
Fail to complete 12 /
20 quizzes
Fail to turn in 5 out of
7 assignments
Come to half the
classes
Nap
1
My Office Hours
Mondays Wednesdays
Module #1
Center of a distribution
Spread of a distribution
Quartiles
5-Number Summary and Boxplot
Outliers
Learning Objectives
By the end of this lecture, you should be able to:
Recognize how scales, mislabeled axes, etc on charts can be misleading
Des
Module 1: Exploratory data analysis
Introduction
Statistics is the science of collecting, analyzing, displaying and
interpreting data. The first question we should ask is: Why
learn statistics?
The NY Times published an article in 2009 titled For Todays
G
Module 1: Examples of exploratory analyses
Example 1: Customer data
A marketing consultant observed 50 consecutive shoppers at a small supermarket. The histogram below
shows the distribution of dollars spent at the store by the customers.
30
25
Percentage
Examples of application of the 68-95-99.7 empirical rule
EXAMPLE 1
A software company finds that the average number of errors in its software per 1000 lines of code is 3
with standard deviation equal to 0.5. Use the 68-95-99.7 rule to answer the following
Syllabus for IT-223
Jeff Grady, MS, MBA
Instructor Information
Instructor: Jeff Grady
Office: CDM 428
Spring 2015
Section number: 601
Class #20036
MW 10:10AM - 11:40AM
LEWIS 1510 Loop Campus
Office Hours: MW 9:15AM-10:00AM
Getting Started
Navigate to the
Creating a boxplot in SPSS
Begin by entering your data. You should have two columns: one for your
dependent variable, and one for your grouping (independent variable).
In the Variable View, make sure that the appropriate scale is selected for each
variabl
Brand
Smucker's Natural
Deaf Smith Arrowhead Mills
Adams 100% Natural
Adams
Laura Scudder's All Natural
Hollywood Natural
Smucker's Natural
Adams 100% Natural
Deaf Smith Arrowhead Mills
Laura Scudder's All Natural
Smucker's Natural
Health Valley 100% Natu
Samir Shallwani
10/11/11
Module 4
1.
a) The confounding variable in this observational experiment would be the 1hour period given to the students to use the application that will help them on
the SAT.
b) In order to eliminate the affect of the compounding
Module 3 project
a. What is the slope of this line? Express in simple language what the slope says about the
relationship of Damage to Distance?
Damage = 10.28 + 4.92 Distance
y= b0 +b1x b0 =intercept, b1 =slope
Slope of the regression line is an impor
Samir Shallwani
IT 223
09/24/11
Module 2
1)
a) 7.65% observes less than 150 hits per hour.
b) The largest number of visits per hour would be 305 hits as that is the most that
can occur given the standard deviation of 35 and mean of 200.
c) 26.25% of times
Samir Shallwani
IT 223
09/17/11
Module 1
1) Describe two categorical variables and two quantitative variables that you might
measure for each customer.
Two Categorical Variables
-Breaking up the users based on gender to see if males are more interested in
Scatterplots
Learning Objectives
By the end of this lecture, you should be able to:
Describe what a scatterplot is
Be comfortable with the terms exaplanatory variable and
response variable.
Describe a scatterplot in terms of form, direction, and
streng
Using the 68-95-99.7 Rule
Normal Quantile Plots
Learning Objectives
By the end of this lecture, you should be able to:
Do various calculations involving areas under the density curve
using the 68-95-99.7 rule
Identify the mathematical technique used to
Thinking about variation
Learning Objectives
By the end of this lecture, you should be able to:
Discuss with an example why it is important to know the variation when analyzing a dataset Interpret a series of Normal curves relative to each other in terms
Module #1 contd
Center of a distribution Spread of a distribution Quartiles 5-Number Summary and Boxplot Outliers
Learning Objectives
By the end of this lecture, you should be able to:
Recognize how scales, mislabeled axes, etc on charts can be misleadin
Samir Shallwani
9/11/11
IT 223
SPSS Lab Activity
Gender
Variables
Mean
St.Dev.
Max
Min
Male
EMAILHR
6.33
9.506
50
0
Female
EMAILHR
5.93
8.884
50
0
Gender
Variables
Median
1st Quartile
3rd Quartile
Male
EMAILHR
2
1
8
Female
EMAILHR
2
1
7
As shown in the ab
IT223
Midterm 20%
DIRECTIONS: Write your name on the Document. During the test save frequently! Explain your
reasoning(s) and Submit your exam on D2L by 11:59pm on Tuesday, October 18th. Dont forget to save a
copy for back up purposes. Dont forget your na