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    Quantative Analysis of Data

    Quantitative analysis is an overarching term used to classify the various characteristics and measures which are utilized in statistics to discuss the behavior of a data set. In many cases, quantitative analyses are conducted to better understand a data set and/or the meaning associated with the results of a particular study. For example, researchers doing a survey on the entrance GPAs held by students applying to law schools would calculate certain quantitative variables such as the mean, to evaluate the average GPA associated with the pool of applicants. Computing measures such as the mean, which is a measure of central tendency, is integral to the study of statistics because it allows data to be interpreted and thus, connected to practical applications. For instance, the previous example considering the mean GPA attained by prospective law school applicants provides a baseline idea of the minimum average a hopeful applicant needs to be competitive when applying to a particular law school. In addition to measures of central tendency, the dispersion and spread of data, along with the distribution of data, are considered when evaluating the features of a data set. The distribution and spread of data considers characteristics such as the standard deviation and interquartile range, which highlight the divergence from a central value or the overall variation. Similarly, the distribution of data examines the total spread of a data set and the departure of a probability distribution from normality. In comparison to other fields of study with seem highly theoretical in nature statistics is very practical and relevant to everyday life. However, in order to properly comprehend the statistical meaning associated with various research studies and data collected, being able to properly analyze the quantitative features associated with raw data is crucial. Thus, quantitative analyses lend context to statistical values. © BrainMass Inc. brainmass.com October 6, 2022, 1:54 pm ad1c9bdddf


    BrainMass Categories within Quantative Analysis of Data

    Central Tendency

    Solutions: 414

    Central tendency typically aims to locate the average value in a set of data and can be measured by calculating the mean, median and/or mode.

    Normal Distribution

    Solutions: 939

    In the study of statistics, the normal distribution is one of the most fundamental concepts and is represented by a graph which is characteristic of a symmetric, bell shaped curve.

    BrainMass Solutions Available for Instant Download

    What are the 99.7% upper and lower control limits

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    Nonparametric Analyses

    What factors should be considered when deciding whether to use a parametric or nonparametric statistical analysis? Identify a research question from your professional life or research interests that could be addressed by a nonparametric statistic. Articulate the variables, scales of measurement, and expected outcome of the study

    Multiple Linear Regression - Job Satisfaction

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    Unit of Analysis and Sample Size

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    Literature Review Quantitatively Measurable Research

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    Research Analysis Set of Hypothesis

    Utilizing any available disclosed database for SPSS, develop a researchable set of hypotheses related to the database. Clearly define quantitatively analyzable hypotheses, analyze your data with SPSS, and write up the results in a full quantitative report format. Draw appropriate conclusions about your hypotheses in your writeup

    Quantitative Article Review

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    Transportation and Assignment Models: Example Problem

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    Factorial ANOVA

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    Index Numbers & Forecasting

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    Decision Theory: Probability Questions

    1. The weight of a one cubic yard bag of landscape mulch is normally distributed with a mean of 40 pounds and a standard deviation of 2 pounds. a. What is the probability that a bag will weigh less than 40 pounds? b. What is the probability that a bag will weigh between 38 and 40 pounds? 2. Accord

    Quantitative vs. Qualitative Data

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    Quantitative Problems in a managerial role and determining expected values

    1. Explain the difference between quantitative and qualitative analysis from the manager's point of view. 2. Explain the difference between mutually exclusive and independent events. Can a pair of events be both mutually exclusive and independent? 3. Explain the transformation from any normal distribution to the standard no

    Financial management, dumping and tariffs

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    Chi-squared tests on SampleDataSet.xlsx

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    Solving linear programming with the graph method

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    Chi-Square with SPSS

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    Covariance Between Age and Number of Visits

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    Probability of Random Letter Selection

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    PSY2007 Sample Question W2A1 can you help with this problem

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    Grading and Evaluation

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    Confidence Intervals for Proportions of M&M's

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    Financial Forecasting Analysis

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    Run Charts Atmospheric Carbon Dioxide Concentrations

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    Skewedness versus kurtosis

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