“Data are summarized in a visual way using charts and graphs (Rumsey, 2010).” Some of the basic graphs used include pie charts, bar charts, and histograms. Pie charts used more for percentages, bar charts used to compare groups and histograms to show numerical data.

Pie charts take data that is categorized and shows percentages or individuals that can be placed into each category. The sum of all pie slices should equal 100 or 100%. Pie charts are in a circular shape which allows slices of the “pie” to be compared easily. An example of a pie chart would be showing where your money goes when you purchase a lottery ticket. A designated amount for prizes, retailers, and the lottery commission itself, and education.

Bar graphs are used also in summarizing data which has been or can be categorized. The bar graph breaks data into groups showing how many pieces are in one group, or what percentage. Bar graphs are often used to compare groups and breaking the groups down and showing the information side by side. An example of a bar graph would be the number of women in the workforce. Breaking that up into number with children, with children under 10 and children 11-17. Units should be evenly spaced when using a bar graph, beware of the scale used and ensure accuracy when plotting graph points, and if bar graphs represent percent’s be sure to include the total number of individuals or items used to obtain the percent’s Histograms are the graph of choice for numerical data. “Histograms provide a quick look at all the data broken down into numerically ordered groups (Rumsey, 2010)”. A histogram is a bar graph that applies to numerical data. Categories in a histogram are ordered small to large. The bars on the histogram touch each other, they do not overlap. This is to ensure that each number only falls in one group. The...

...Charts and graph are images that present data symbolically. They are used to present information and numerical data in a simple, compact format. This paper will focus on three types of charts and/or graphs which are: pie charts, bar graphs, and histograms.
What types of data there are and how the data was collected is important for the reader to understand.. According to Bennett, Briggs, and Triola (2003) there are two types of data. They are:
*Qualitative data- Data consisting of values that describe qualities or nonnumeric categories.
*Quantitative data- Data consisting of values representing counts or measurements (p G-4).
In the following three examples of charts/graphs the type of data being displayed will be discussed.
Pie Chart
Excellent use of section headings!
The first type to be discussed is a pie chart. A pie chart is "a circle divided so that each wedge represents the relative frequency of a particular category. The wedge size is proportional to the relative frequency, and the entire pie represents the total relative frequency of 100%" (Bennett et al., 2003, p G-3).
This first chart displays the results of a 60-day survey to determine the amount of library users conducting searches within the nursing profession (Jones, 2006, p 1). Excellent citations throughout your...

...Doreen Carranza
HCS/438
Biman Ghosh
Sample of Chart or Graph Assignment
1/21/2013
Health Care Spending Demographics
U.S. households spent, on average, a total of $2,976 on health insurance, medical services, drugs, and medical supplies in 2008. Hispanic, Black or African American, and Asian households spent less—and White households spent somewhat more–than the average. These averages are calculated with data collected from all types of households; that is, households of all sizes, ages, incomes, etc., including both households that pay for insurance as well as those that do not. The amount spent on insurance does not include any portion paid by employers or government.
• The type of chart shown above is called a Bar graph. Bar graphs are used to summarize data which has been or can be categorized. The bar graph breaks data into groups showing how many pieces are in one group, or what percentage. Bar graphs usually present categorical and numeric variables grouped in class intervals. They consist of an axis and a series or labeled horizontal or vertical bars. The bars depict frequencies of different values of a variable or simply the different values themselves.
• I believe that this was a proper graph used to present the data. The information is clear and concise. The data was presented in a good...

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1. Name three different kinds of graphs that are often used to plot information and discuss the value of each.
Answer:
Three types of graphs are line graph, histogram or bar graph, and pie chartgraph.
The line graph is used to describe how an object moves explaining relationship between time and distance traveled.
A histogram or bargraph is used to compare quantities using a series of vertical bars.
A pie chartgraph represents data in a chart that resembles a pie cut into pieces. This is valuable when comparison to the whole is important.
Each type of graph presents information in a visual manner, which often makes interpretation more interesting.
(7 points)
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2. Explain what chart junk is and how it differs from the kind of items you should include in your graphs. Provide four examples.
Answer:
Chart junk consists of decorative and distracting elements added to a graph that do not supply useful information on the graph such as texture or designs in the bars of a bar graph.
These may include strange highlighting or coloration, unusual formatting, cartoon drawings or pictures placed into the...

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Statistics
BUS308: Statistics for Mangers
Instructor:
Learning Statistics
Statistical data has become an item that we see all around us in our everyday lives, from television programs talking about selling products or politicians using data to show how they perform in their jobs, in hopes to be reelected. Throughout the course in Statistics for Managers, I have learned many things on how the use of statistical information can help me to understand these items and also to help me to perform my job and understand the day-to-day operation of the company. With the use of statistics, anyone can find out information and details on most anything, allowing them to understand a business better or to make better decisions in their everyday life. Because statistics is all around us, using and understanding this information is important to find answers to questions, to make better decisions, and understand how things work.
Some of the types of information I have learned to use is through the use of descriptive and inferential statistics. According to the textbook for statistics, “descriptive characteristics can provide a great economy when data sets are large. Inferential statistics are utilized when the sample’s characteristics are important for what they reveal about the entire population”. (Tanner & Youssef-Morgan, 2013) Even though there are...

...techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of data analysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to infer the...

...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...

...2014-02-04
Chapter 2 Learning Objectives (LOs)
LO 2.1: Summarize qualitative data by forming
frequency distributions.
LO 2.2: Construct and interpret pie charts and bar
charts.
LO 2.3: Summarize quantitative data by forming
frequency distributions.
LO 2.4: Construct and interpret histograms, polygons,
and ogives.
LO 2.5: Construct and interpret a stem-and-leaf
diagram.
LO 2.6: Construct and interpret a scatterplot.
McGraw-Hill/Irwin
2-2
House Prices in Southern California
House Prices in Southern California
A relocation specialist for a real estate firm in
Mission Viejo, CA gathers recent house sales
data for a client from Seattle, WA.
The table below shows the sale price (in
$1,000s) for 36 single-family houses.
Use the sample information to:
1. Summarize the range of house prices.
2. Comment on where house prices tend to cluster.
3. Calculate percentages to compare house prices.
2-3
2-4
1
2014-02-04
2.1 Summarizing Qualitative Data
LO 2.1
LO 2.1 Summarize qualitative data by forming frequency distributions.
A frequency distribution for qualitative data
groups data into categories and records how many
observations fall into each category.
Weather conditions in Seattle, WA during
February 2010.
2.1 Summarizing Qualitative Data
Categories: Rainy, Sunny, or Cloudy.
For each category’s frequency, count the days
that fall in that category....

...H5 was ruled out for the alpha being greater than the P-value for the age at which the first claim occurred.
The P-value for H1 and H3 both have an alpha level which is less than the P-value. However, we have compared how age of the patient affects H1 & H3. We have created two subsets using our independent variables. The patients in H6 are ages 0-39. H7 contains the same independent variables, however, the patients are over the age of 40. We have found that for patients aged 0-39 have a greater increase in days in the hospital as drug count and visit count increase. In comparison, patients age 40 and over spend a less number of days in the hospital.
The remainder of our analysis will focus on H6 & H7.
Methods: Descriptive Statistics
1. Demographics of Data Collection and Operationalization of the Variables
The study population consists of:
PEOPLE AGES (at the first time of service):
* 0-39 years old
DRUG COUNT: Number of Drugs Administered at First Service
VISIT COUNT: Number of hospital visits in Year 1
(See Appendix A.)
Data Syntheses: There is a definite relationship between the independent variables and the hypotheses tested. We tested a sample size (n= 8356) of patients who volunteered their information. We concluded that the strongest correlation exists between the visit count and the number of days spent in the hospital.
For H7 the P-value for visit count is .000. The P-value for drug count is .000.
Results: (n=8356)...