# Examples Of Descriptive Statistics

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Introduction
Statistics is the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample. The following paper seeks to provide basic knowledge in some specific areas of statistical data analysis.
Descriptive statistics
Descriptive statistics is the term given to the analysis of data that helps describe, show or summarize data in a meaningful way. Descriptive statistics do not allow us to make conclusions beyond the data we have analyzed or reach conclusions regarding any hypotheses we might have made. They are just simply a way to describe our data. When data is presented to its users, it can be hard to understand
In this case, the frequency distribution is simply the distribution and pattern of marks scored by the 100 students from the lowest to the highest. We can describe this central position using a number of statistics, including the mode, median, and mean.
Measures of dispersion: Measures of dispersion are ways of summarizing a group of data by describing how spread out the scores are. For example, the mean score of our 100 students may be 65 out of 100. However, not all students will have scored 65 marks. The scores will be spread out. Some will be lower and others higher. Measures of spread help us to summarize how spread out these scores are. Range, standard deviation, quartiles, absolute deviation and variance are some of the measures of dispersion.
Inferential
There are several different types of statistical testing to choose from depending on whether the data follows normal distribution and the aim of the study. You have to define the level of measurement of each variable to be included in the analysis. Usually data is in one of the following four categories: Nominal data, Ordinal data, Interval data and Ratio data. Aim of the study is another pre-requisite that must be clearly defined for the selection of statistical test (Jaykaran). Next, is to select the correct statistical analysis, you have to clarify what you want to find out. The research question or hypothesis is typically phrased in terms of finding differences, relationships, or predicting. For relationship questions with interval, ordinal-level, or ratio-level variables, the correct statistical analysis is typically Spearman or Pearson correlations. Lastly, the sample size calculation or power analysis is directly related to the statistical test that is chosen. The sample size calculation is based on the power, the effect size, and the

• ## Importance Of Quantitative Methods

Quantitative Methods The main aim of this paper is to discuss what are statistics, quantitative methods, and data analysis, and why do we need them. We will also discuss the importance of patterns and variations within data and how they can be analyzed to be presented in a way that affects real life products such as public policy. Though an established science, some quantitative method practices are criticized through epistemological considerations, particularly, the positivism position. The concerns raised by this position will also be considered in this paper as it raises important views on the subject. Lastly, we will set an example on how data analysis could affect public policy, prior to the conclusion.…

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• ## The Chi Square Test Analysis

Chi square test is used when sample size is large. Chi-square symbolically written as χ2 is a statistical measure used in the context of sampling analysis for comparing the variance to a theoretical variance. The test is in fact a technique through the use of which it is possible for the researcher to test the significance of association between two variables. Factor Analysis Factor Analysis is a multivariate statistical method whose primary purpose is to define a structure within a set of observed…

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• ## Units Of Enumeration Essay

They differ in many aspects like the role assigned to them in the research and in the type of measures that can be applied to them. Measures in descriptive statistics to describe the data set under investigation include measures of central tendency and measures of variability. A measure of central tendency is a single value that attempts to describe a set of data by identifying the central position. The measures of central tendency include mean, median and mode. The mean is equal to the sum of all the values in the data set divided by the number of values in the data set.…

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• ## Kahmandu Descriptive Research Design

The main goal of this type of research is to describe the data and characteristics about what is being studied. The idea behind this type of research is to study frequencies, averages, and other statistical calculations. Sample Designing :> After defining the problem . Do work on research design and determine how to collect the data. The next step is to decide who should be survey (sample u need), how many and how they should be chosen.…

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• ## Ace Inc Case Study Answers

Ace would like to examine this data in order to prepare analysis report to the management team. Statistical Results 1. In this study of test scores and took statistics course, each variable in the sample data is characterized by creating a histogram and pie chart, respectively. According to…

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• ## Serial Correlation And Deletion And Mean Squared Error Compression Technique

Introduction. Serial correlation can be defined as a relationship between elements within a time series. It can affect the variance of our estimators, and cause us to incorrectly estimate our true mean, Y ̅. To properly study and analyze a covariance stationary time series, we need to know something about the correlation/covariance structure. Several methods exist for dealing with serial correlation.…

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• ## Regression Analysis In Statistics

To the degree that it is based on counting various pairs in a relationship. Known as a statistical tool that investigates relationships among variables, regression analysis seeks to determine the unintended effect of one variable to another. This is typically a relationship between the dependent variable and one or more independent variables.…

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• ## Compare And Contrast The PF And Traditional Models Of Validityity

In the process-focused model, the concept of validity is based in the degree to which respondents to participate in predictable psychological process in the time of assessment. While in traditional validity model the concept of validity is based on the correlational methods used in qualifying the relationship between test score and criterion. The process-focused model used experimental methods for the purpose coming up with variables that show the relationship between the test score and the criterion which will enable the researcher to draw better understanding. The traditional validity method does not use experimental methods. The process-focused model puts empirical emphasis which enables the researcher to manipulate variable hence helping the researcher draw conclusions, impacts of the process among others while traditional approach does not it only depends on the outcome.…

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• ## Examples Of Quantitative Research

This kind of research centers between quantitative and qualitative research. It seeks to incorporate the strengths of both in pursuit of a more holistic view of the test subject. Creswell (2013) defines this type of research well by saying, “Mixed Methods research is an approach to inquiry involving collecting both quantitative and qualitative data, integrating the two forms of data, and using distinct designs that may involve philosophical assumptions and theoretical frameworks” (p. 4). Mixed Methods pretty much follows the respective approaches for quantitative and qualitative research. A deviation from the other methods of research is how the results are interpreted.…

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• ## Quantitative Research Methodology

Fraenkel and wallen (2000) suggest that in correlation research the researcher investigates a set of data to find out whether the relationship between variables exists or not, and researcher examines the association which exists in the natural state without influencing the respondents. On the other hand, casual research includes the collection of clusters with identified differences and determinesthe variables that may create the difference. Fraenkel and Wallen (2000) describe another type of quantitative research which is known as experimental methods that is most appropriate for analysis or investigating hypothetical model and observe causation. This type of quantitative research permits the examiner to find out the changes which affect the desired outcomes. In short, there are many…

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