Vocabulary Dat Video Analysis

A statistical example for random variable is coin toss that refers to the discrete random variable as it will get the outcomes in discrete number.

Third is the interval level of measure, at this level we can do mathematics with the numbers. There is still no zero point. A video by J. David Eisenberg on you tube, gave a great example, that I will share with you, the link will be provided in the reference section. J. D. Eisenberg stipulates the following: one person is 176 cm tall, the other is 170 cm tall, and it is evident that one is taller than the other, 170 cm + 6 cm = 176cm. Arithmetic is meaningful. The difference or interval is also

Quantitative has values of numbers or measurements. Quantitative is represented by numbers and the number of people on a jury always ranges from 6 to 12. It means that there is a count of people that are needed on a jury.

Quantitative data deals more with, “providing a measure of how many people think, feel or behave

Categorical variables are observations that can be sorted into categories like age or gender. Quantitative variables are observations that can be measured like size or weight. In this experiment the categorical variable was the age and gender of my participants. The quantitative value was the size of the blindspot when measured. (Statistics, n.d.)

ased on all the information that I’ve learned in the class and in the texted book. Now understanding more about mnemonics was difficult for me, but being in class and watching the video, explains it better for me. Putting meaning to word or sentences that I can relate to will help me remember things better in the long-term. For explain when the Ron White the memory champion, talking about the man with the big nose, I thought it was funny. It reminded me a friend of mind and now I can relate to that. Watching him pick out things that he saw in people like the color of their outfit or a small detail in their appearance. I will be able to use the same tricks in my studying for the next exam.

Statistics is defined as collecting,summarizing,organizing and analyzing the data. For instance, astro-statistics deals with statistical study and analysis

"Descriptive statistics is the summary of important aspects of a data set" (Jaggia & Kelly, 2014). To use descriptive statistics, I would use frequency distribution. "Frequency distribution of qualitative data groups the data into categories then records the number of observations that fall into each category" (Jaggia & Kelly, 2014). If I use ordinal data, it will allow us to categorize and rank the data. The data will then enable us to determine if recognition will help the high turnover rate at UnitedHealth Group.

Data are the facts and figures that are collected, analyzed, and summarized for presentation and interpretation. Statistics was developed in the early 19th century as the study of populations, economies, and moral actions and later in that century as the mathematical tool for analyzing such numbers. Examples of Statistics that are used today are Mean, Median ,Mode and Range, Histograms and Stem and leaf plots. Sample survey methods are used to collect data from observational studies, and experimental design methods are used to collect data from experimental studies. The area of descriptive statistics is concerned primarily with methods of presenting and interpreting data using graphs, tables, and numerical summaries. Whenever statisticians use data from a sample., a subset of the population—to make statements about a population, they are performing statistical inference. The population is how many people i'm doing for my project which is 50 people. Estimation and hypothesis testing are procedures used to make statistical conclusions. Probability plays a key role in statistical inference, it is used to provide measures of the quality and precision of the inferences. Some of these methods are used primarily for single-variable studies, while others, such as regression and correlation analysis, are used to make inferences about relationships among two or more variables. A paradox is a statement that, despite apparently sound reasoning from true premises, leads to a self-contradictory or a logically unacceptable conclusion. The purpose of a paradox is to arrest attention and provoke fresh thought. An entertaining example is to determine the probability that in a randomly selected group of n people at least two have the same birthday. If one assumes for simplicity that a year contains 365 days and that each day is equally likely to be the birthday of a randomly selected person, then

Quantitative information is information that can be directly measured and can be seen as factual information rather than an opinion, this is usually hard to argue with.

Elementary school students across the nation have encountered a statistical situation in one form or another without ever realizing it. Many students in elementary grades, as well as upper-level students, tend to avoid questions dealing with statistics. In the article, “Statistics in the Elementary Grades: Exploring Distributions of Data” authors Christine A. Franklin and Denise S. Mewborn provide teachers with a four step process to help students have a better understanding of statistics.

Statistics is a comparison of two numbers, one from a current standpoint and one from a previous time frame. In the real world, there are many ways to measure observations or responses using a mathematical analysis. By collecting this information, analyzing the data and then summarizing it with the use of numbers helps people, businesses and consumers drive decisions. There are many ways to collect statistics through surveys and other data collections. An example of this is when consumers shop, they often swipe their loyalty cards and provide stores information on items purchased and consumer shopping patterns.

Encyclopedia Britannica defines Quantitative data as a “measure either how much or how many of something” and qualitative data as data that “provide labels, or names, for categories of like items” (Qualitative data, 2011). Those who are not familiar in the field would not understand these terms or the study. Someone who is knowledgeable in the social science field would understand this study, which is why the authors use this specialized vocabulary (Guerra, et al. 2011).

I will be doing a bar graph on the amount of candy produce daily. “A bar graph consists of bars representing frequencies (or relative frequencies) for particular categories” (Bennett,2012, p. 87).

2) For each variable that you identify as quantitative, state whether it is discrete or continuous.