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Descriptive Statistics

Descriptive statistics is the process of summarizing data in both a quantitative and visual manner. In a quantitative sense, typically this involves highlighting the main elements of a collection of data, for example, calculating the mean, median and mode. It is through the construction of figures, such as histograms and pie charts that data can be visually represented. Essentially, the overarching goal with descriptive statistics is to characterize data so that the basic quantitative features can be properly understood.

In descriptive statistics, the method which is utilized to express data depends on the type of data which is being analyzed. Simply put, data can be separated into two general groups: categorical data and numerical data. When dealing with categorical data, the variables which are measured are usually either nominal or ordinal in nature. A nominal variable is one representative of a category, with no associated numerical value. For example, data collected on the different colours of hummingbirds in a sample would represent nominal data. However, ordinal variables do have associated intrinsic values, usually classified as levels or rankings. For example, pretend that in the hummingbird scenario only yellow hummingbirds were measured in terms of the intensity of yellow which they possessed, either being low, medium or high. Therefore, these three levels of intensity would represent ordinal variables.

In comparison to categorical data, numerical data classifies variables as being either continuous or discrete. Discrete variables are whole numbers, whereas, continuous variables can resemble any number within a range.

Descriptive statistics is an integral part to the analysis of data because it allows data to be represented in a visual way, in which patterns and outliers can be identified. The use of descriptive statistics is useful for any study which aims to describe the characteristics of the different measures being collected. Additionally, it is critical to understand that descriptive statistics does not aim to formulate inferences which extend beyond the sample data being studied to the population at large. Rather, it functions to solely evaluate and visualize the immediate data collected.

Categories within Descriptive Statistics

Coefficients for both simple and multiple regressions

1. A professor wants to test if the number of sunny days in the week before an exam has an influence on student grades .A sample of 20 is taken and the following regression equation is obtained. Y = 80 - .5X S b1 = .1 a) Test at a=.05 b) Interpret R2 2. Given the following regression equation for a sample of 3

Graphical & Tabular Descriptive Summaries

Using the attached excel file, identify and discuss what makes a Crusty Pizza Company restaurant successful and conversely unsuccessful. Use the data for the 60 stores in worksheet "Case 1 and 2 data". Use graphical and tabular descriptive statistics. Plan the analysis by using a combination of summaries that best allow you to

Frequency Distribution with Skewed Data

1. Identify three uses for a frequency distribution. Please provide realistic health related examples. 2. Briefly identify the differences between a normal, positive and negative skew. How does this skew or distribution curve relate to standard error? What does the standard error mean for the results? Feel free to use and exa

Deviation of Plastic Sheets

Plastic sheets are manufactured on your blown film line. The Cp value is 1.7. You sell the plastic sheets to your customers with specification of 2 mm ± 0.4 mm. 1. List three important assumptions you must make to interpret the Cp value. 2. What is the theoretical process standard deviation, σ? 3. What would be the Shewhar

Assumptions, Calculations, and Confidence Interval for Means

Your manager is asking for the average viscosity of a product that you produce in a batch process. Recorded below are the 12 most recent values, taken from consecutive batches. State any assumptions, and clearly show the calculations that are required to estimate a 95% confidence interval for the mean. Interpret that confidenc

Descriptive Statistics, Reliability and Validity

1. Reliability vs. Validity. Considering your area of research interest, discuss the importance of reliability and validity. Can you have one without the other? Why or why not? 2. Sample vs. Population. Considering your area of research interest, describe the difference between a sample and population. Why is it important to un


1. The frequency distribution below was constructed from data collected on the quarts of soft drinks consumed per week by 20 students. Quarts of Soft Drink Frequency 0 - 3 4 4 - 7 5 8 - 11 6 12 - 15 3 16 - 19 2 a. Construct a relative frequency distribution. b. Construct a cumulative frequ

T-Statistics: Standard Errors

W. Bowen and T. Finegan (1965) published a paper titled "Labor Force Participation and Unemployment." In that paper they estimated the following regression using a data set of 78 cities: i = 94.2 - .24Ui + .2Ei -.69Ii - .06Si + .002Ci - .8Di (.08) (.06) (.16) (.18) (.03) (.43) The standard errors for the OLS coefficient

Regression Analysis - Statistics and Minitab

Management of a soft-drink botling company wishes to develop a method for alocating delivery coststo customers. Although part of total cost clearly relates to travel time within a particular oute, another variable reflects the time required to unload the cases of soft drink athe delivery point. A sample of 20 customers was se

Hypothesis Testing and One-Tailed Test

I need some help with this question: An increased number of colleges have been using online resources to research applicants. According to a study from last year ,31% of admissions officers indicated that they visited an applying student's social networking page. A random sample of 400 admissions officers were recently select

Finding 98% and 99% Confidence Intervals

1. What is the 99% confidence interval for the variance of exam scores for 25 algebra students, if the standard deviation of their last exam was 10.7? 2. In a sample of 60 mice, a biologist found that 42% were able to run a maze in 30 seconds or less. find the 98% limit for the population proportion of mice who can run that maz

Probability, confidence interval, analysis sample questions

The area under the normal curve between z=1 and z=2 is ________________ the area under the normal curve between z=2 and z=3. A. Greater than B. Less than C. Equal to D. A, B or C above dependent on the value of the mean E. A, B or C above dependent on the value of the standard deviation Essay Type Questions Please s

Solving 30 Questions on Descriptive Statistics

Answer all 30 questions. Make sure your answers are as complete as possible. Show all of your work and reasoning. In particular, when there are calculations involved, you must show how you come up with your answers with critical work and/or necessary tables. Answers that come straight from programs or software packages will not

Computing Prevalence and Incidence of Diabetes

In a nursing home, a program is launched in 2005 to assess the extent to which its residents are affected by diabetes. Each resident has a blood test and 48 of the 625 residents have diabetes in 2005. Residents who did not already have diabetes were again tested in 2010 and 57 residents had diabetes. What is the prevalence

Computing probability using Poisson model and classical model

7. A call center receives about 4 calls every minute during peak time. (a) What is the probability that the call center will receive 3 or more calls during a peak minute? (b) If peak time spans 15 minutes, what is the probability that 50 calls will be received during this time period? 8. Six cards are chosen without replac

Stets on solving some questions on descriptive statistics

1) Calculate arithmetic mean of:  a. Wages: 75, 100, 120, 150, 200 Total b. Workers: 5, 12, 20, 14, 9 60 2) Calculate the median age:  a. Age Years (Less than): 10, 20, 30, 40, 50, 60, 70, 80 b. No. of persons: 4, 16, 40, 76, 96, 112, 120, 125 3) Calculate Spearman's Rank Correlation:  a. Trainees: A, B, C, D, E, F

SPSS Analysis of Data

The Stat_Grades.sav dataset contains data collected about statistics students in three sections of a statistics class taught by an instructor. I attached specific research questions for the analysis along with the dataset. A solution would assist me in understanding descriptive statistics better.

Independent T-test and SPSS Data Interpretation

Please review and answer the following questions with short explanations for answers. Review the SPSS output file which reports the results of the independent t-test to compare the mean price per 6-pack for regular vs. reduced calorie brands of wheat beer. Answer the following questions based on your observations of the SPSS

stats help

28) police response time to an emergency call is the difference between the time the call is first received by the dispatcher and the time a patrol car radios that it has arrived at the scene. Over a long period of time, it has been determined that the response time has a normal distribution with a mean of 8.4 minutes and a stan

Statistics: Testing Hypotheses

The attached file contains the yield for a money market account, a one-year certificate of deposit (CD), and a five-year CD for 23 banks. a) At the 0.05 level of significance, is there evidence of a difference in the mean yield of the different accounts? b) If appropriate, determine which accounts differ in mean yields. c)

MCQs: Probability Questions

21) In the first full day of the NCAA basketball tournament 16 games are played. What is the probability of selecting every game correctly (i.e., picking the eight winning teams) for the first full day of the tournament? A. 0.5 B. 0.00008 C. 0.0075 D. 0.8 22) How many different ways could the 32 cars in a NASCAR race fi


A) SPSS and Data Summary: From the dataset attach, select any two quantitative variables. What is the name of your two quantitative variables you will be analyzing? Use SPSS to compute summary (descriptive) statistics, including measures of central tendency mean, median, mode and numerical measures variance and standard devia

When the Mode is Better Than the Mean

1) When is "mode" the better measure? Think about what you have learned and how you can relate it to your profession, your daily life, or a realistic hypothetical situation. 2) Then, create (invent) a realistic small dataset that can be best described by mode and poorly described by mean. 3) List the dataset. 4)