Homework #1 STAT
Note: Homework should be printed before class. 25 points
Instructions: This assignment involves applying various techniques that we have covered throughout the semester using MINITAB 16. You will be using data sets that come with MINITAB 16. Click on the icon “Look in Minitab Sample Data Folder” to access data files. You will see data sets and several folders that contain the data. To receive full credit, be sure to include relevant computer output (copy and paste into a WORD document) and provide interpretations when asked. You are to work independently. You will need to use the help feature in order to read the data set descriptions and provide meaningful comments. 1. Use the data set TVHOURS.MTW in the Student14 folder.

a) Prepare a pie chart for the variable “Educ.” Comment on the results. b) Prepare a segmented bar chart to examine “Educ” by “Gender.” Comment on the results. c) Prepare a histogram for the variable “HrsTV.” Comment on the shape of the distribution. d) Show descriptive statistics on the variable “HrsNews” for all age groups. Use the optional “By Variables” box; enter “AgeGrp” in the box. Comment on the results. Make sure to compare the distributions across age group commenting on central tendency and variability.

2. Use the data set SEASONALSALES.MTW.

a) Show descriptive statistics for the variable “Daily Sales” for each season. Use the optional “By Variables” box; enter “Seasons” in the box. Compute the range and IQR for each season as well. Comment on the results. b) Prepare boxplots of “Daily Sales” for each season showing them on the same graph. Choose the options “One Y” and “With Groups.” Graph the variable “Daily Sales” and use “Season” as the categorical variable for grouping. Do the boxplots agree with your comments in part (a)? Explain.

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t like this...

...compliments the regular mathematics and therefore both are tested in primary schools. Mathematics is the written application of operation. It teaches students to think clearly, reason well and strategize effectively. Mental Mathematics is the ability to utilise mathematical skills to solve problems mentally. The marks scored by pupils generate statistics which are used by teachers to analyse a student’s performance and development of theories to explain the differences in performance.
The Standard 3 class is where the transition from junior to senior level occurs where teachers expect the transference of concrete to abstract thinking would have occurred.
A common theory by many primary school teachers is ‘Students perform better in Mathematics than Mental math. Mental math is something that has to be developed and involves critical thinking. Mental math requires quick thinking and the student must solve the problem in their minds whereas in regular mathematics, the problem can be solved visually. Therefore, teachers should take these factors into consideration while testing and marking students in these areas.’
In this study, the statistics of 30 students of a standard 3 class of San Fernando Boys’ Government School will be analysed to determine the truth of this theory.
DATA COLLECTION METHODS
Mathematics and mental mathematics marks of term 1 of the class of 2013 were obtained from a Standard 3 teacher of San Fernando Boys’...

...Alexander College
Comm 291
Assignment 1
Instructor: Alfred Kong
Due date: 26th May 2014
The assignment is due at the beginning of the class. Late assignment will not be accepted.
For this assignment, complete all of the following questions.
Question 1
A manufacturer of cat food was planning to survey households in the US to determine purchasing habits of cat owners. Among the questions to be included are those that relate to
1. Where cat fat is primarily purchased.
2. Whether dry or moist cat food is purchased.
3. The number of cats living in the household.
4. Whether the cat is pedigreed.
a. Describe the population.
b. For each of the four items listed, indicate whether the variable is categorical or numerical.
Question 2
One of the major measures of the quality of service provided by any organization is the speed with which the organization responds to customer complaints. A large family-held department selling furniture and flooring, including carpet, had undergone a major expansion in the past several years. In particular, the flooring department had expanded from 2 installation crews to an installation supervisor, a measurer, and 15 installation crews. During a recent year, the company got 50 complaints concerning carpet installation. The following data represent the number of days between the receipt of the complaint and the resolution of the complaint:...

...Types of Variables
Binary variable
Obsevations (i.e., dependent variables) that occur in one of two possible states, often labelled zero and one. E.g., “improved/not improved” and “completed task/failed to complete task.” Usually an independent or predictor variable that contains values indicating membership in one of several possible categories. E.g., gender (male or female), marital status (married, single, divorced, widowed). The categories are often assigned numerical values used as lables, e.g., 0 = male; 1 = female. Synonym for nominal variable. A variable that obscures the effects of another variable. If one elementary reading teacher used used a phonics textbook in her class and another instructor used a whole language textbook in his class, and students in the two classes were given achievement tests to see how well they read, the independent variables (teacher effectiveness and textbooks) would be confounded. There is no way to determine if differences in reading between the two classes were caused by either or both of the independent variables. A variable that is not restricted to particular values (other than limited by the accuracy of the measuring instrument). E.g., reaction time, neuroticism, IQ. Equal size intervals on different parts of the scale are assumed, if not demonstrated. Synonym for interval...

...Mass movement (india) 1920 to 1942
The idea of Satyagraha
Mahatma Gandhi returned to India in January 1915. As you know he had come from South Africa when he had successfully fought the racist regime with a novel method of mass agitation, which he called Satyagraha. The idea of Satyagraha emphasized the power of truth and the need to search for truth. It suggested that if the cause was true, if the struggle was against injustice, then physical force was not necessary to fight the oppressor. Without seeking vengeance or being aggressive a Satyagrahi could win the battle through non-violence. Appealing to the conscience of the oppressor could do this. People – including the oppressors – had to be persuaded to see the truth instead of being forced to accept the truth through the use of violence. By this struggle, truth was bound to ultimately triumph. Mahatma Gandhi believed that this dharma of non-violence could unite the Indians.
After arriving in India, Mahatma Gandhi successfully organized Satyagraha movements in various places. In 1916, he went to Chamaparan in Bihar to inspire peasants to struggle against oppressive plantation system. Then in 1917, a struggle was organized to support peasants of Kheda district in Gujarat, affected by crop failure and a plague epidemic. In 1918, he went to Ahmadabad to organize a movement amongst the cotton mill workers.
The Rowlatt Act
Emboldened by these successes, in 1919 Gandhi decided to launch a nation wide...

...Department of Management Faculty of Management and Human Resource Development
SUBJECT:
SHD 1713: STATISTIC 1
LECTURER:
DR, LOW HOCK HENG
PREPARED BY:
NOOR AZNEE BINTI JUNAIDI ZULFADLY BIN SAIFUL MOHD RASYDUDDIN BIN MAT NAWI MOHD HAZRUL AZEWAN MOHD ASRI BIN MOHD ARIFIN MOHD FAKERRYIKMAL BIN KAMALUDIN 820423-12-5184 870314-56-5549 830503-03-5829 810406-01-5451 750203-08-5159 890417-59-5265 SX110698HDS04 SX110718HDS04 SX110686HDS04 SX105341HDD04 SX112315HDF04 SX112317HDF04
1.
A researcher has collected data on a sample of 2,000 eels in Pacific Ocean. The researcher measured the length of those eels and develops the following relative distribution:
Class Length (cm) 25 to less than 30 30 to less than 35 35 to less than 40 40 to less than 45 45 to less than 50 50 to less than 55 55 to less than 60 Relative Frequency, fi 0.22 0.15 0.25 0.24 0.06 0.05 0.03
Develop a frequency distribution from the data above. Calculate the mean as weel.
Answer:
Class Length (cm) 25 to less than 30 30 to less than 35 35 to less than 40 40 to less than 45 45 to less than 50 50 to less than 55 55 to less than 60 Total
Midpoints, m 27.5 32.5 37.5 42.5 47.5 52.5 57.5
Frequency, f 440 300 500 480 120 100 60 2000
Relative Frequency, fi 0.22 0.15 0.25 0.24 0.06 0.05 0.03 1
Percentage 22 15 25 24 6 5 3 100
mf 12100 9750 18750 20400 5700 5250 3450 75400
c
∑m f
Mean from a frequency distribution , X =
j=1
j j
n
= 75400 2000
X = 37.7...

...Time | Contributor | Contribution |
Ancient Greece | Philosophers | Ideas - no quantitative analyses |
17th Century | Graunt,Petty
Pascal, Bernoulli | studied affairs of state, vital statistics of populations studied probability through games of chance, gambling |
18th Century | Laplace, Gauss | normal curve, regression through study of astronomy |
19th Century | Quetelet
Galton | astronomer who first applied statistical analyses to human biologystudied genetic variation in humans(used regression and correlation) |
20th Century (early) | PearsonGossett (Student)
Fisher | studied natural selection using correlation, formed first academic department of statistics, Biometrika journal, helped develop the Chi Square analysisstudied process of brewing, alerted the statistics community about problems with small sample sizes, developed Student's testevolutionary biologists - developed ANOVA, stressed the importance of experimental design |
20th Century (later) | Wilcoxon
Kruskal, Wallis
Spearman
Kendall
Tukey
Dunnett
Keuls
Computer Technology | biochemist studied pesticides, non-parametric equivalent of two-samples testeconomists who developed the non-parametric equivalent of the ANOVApsychologist who developed a non-parametric equivalent of the correlation coefficientstatistician who developed another non-parametric equivalent the correlation coefficientstatistician who developed multiple comparisons...

... |
|Course Title |Descriptive and Inferential Statistics |
|Prerequisite |MTHS001 (College Algebra) |
|Credit/No. of Units |3 units |
|Duration/Term |First Semester, School Year 2012 - 2013 |
|Instructor |Glenda G. Quinto |
|E-mail Address |alphakristina916@yahoo.com |
|Consultation Hours |9:00am-10:30am TTh; 3:00pm – 4:30pm MW; 9:00am-10:30am T |
|Consultation Venue |CAS Faculty Lounge, 1st Floor, Dolan Building |
Course Outline
I. Nature of Statistics
1. Introduction to Statistics
2. Descriptive and Inferential Statistics
3. Variables and Types of Data
4. Data Collection and Sampling Techniques
5. Observational and Experimental Studies
6. Uses and Misuses of Statistics...

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