Techniques for summarizing quantitative data

The TV has been on for the last 1, Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more. Only repeated trials of the most rigorous and controlled experiments can provide standard proof of a cause-effect relationship.

Organizing Your Social Sciences Research Paper: Quantitative Methods

Case study The case study technique involves focusing on a particular individual, organization or group, such as a corporation, non-profit agency or religious cult, to name a few. There are also quasi-experimental techniques that are less rigorous and controlled than so-called true experiments. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view.

Keep figures small in size; include graphic representations of confidence intervals whenever possible. Below is a table showing these 4 measurement scales and across the top are the 4 features that distinguish them.

Summary The first important aspect of any statistical analysis is an appropriate summary of the key analytic variables. The written account of the research is often referred to as ethnography, a rich descriptive account of the field experiences typically incorporating photographic images and diagrams, maps, stories and so on.

The numbers look discrete, but they are technically continuous. Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study. Meta-analysis Also known systematic review or best-evidence synthesis and very closely related to secondary analysis, this technique involves pooling a collection of high-quality published studies and systematically reviewing the combined evidence.

Construct a frequency distribution from a set of data Construct different types of quantitative data graphs, including histograms, frequency polygons, ogives, dot plots, and stem-and-leaf plots, in order to interpret the data being graphed Construct different types of qualitative data graphs, including pie charts, bar graphs, and Pareto charts, in order to interpret the data being graphed Recognize basic trends in two-variable scatter plots of numerical data Container Shipping Companies For decades, business people in many countries around the world wrestled with the issue of how to store and ship goods via trucks, trains, and ships.

In the Interval scale, the distances between values are equal and consistent. It is important to identify whether the data are quantitative or qualitative as this affects the statistics that can be produced. For example, the relative frequency for the first class For example, if we had the results of pieces of students' coursework, we may be interested in the overall performance of those students.

However, when taking height into account by comparing body mass index instead of comparing weights alonewe see that the most extreme outliers are among the women. Bates College; Nenty, H. You can think of the relative frequency histogram serving as a sample estimate of the true probabilities of the population.

Data Accuracy is the degree to which an individual data point or set of data agrees with an accepted standard or reference value. Popular with marketing and polling firms, it can be used to ascertain the needs and concerns of consumers with regard to a trial product or a new political candidate or policy.

Mode can be calculated, as it it the most frequency observed value. The methods of inferential statistics are 1 the estimation of parameter s and 2 testing of statistical hypotheses.

Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail; Uses a static and rigid approach and so employs an inflexible process of discovery; The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject; Results provide less detail on behavior, attitudes, and motivation; Researcher may collect a much narrower and sometimes superficial dataset; Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception; The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise.

However the distance between 1st and 2nd is not always the same as the distance between 2nd and 3rd place. The graphs below arrange the quantitative and qualitative data to show the frequency distribution of the data. For example, if you were only interested in the exam marks of students, the students would represent your population.

Here is what the density histogram would like in its entirety: Data collection methods — Describe various methods for collecting data, including tally or check sheets, data coding, automatic gaging, etc.

A sample of 40 female statistics students were asked how many times they cried in the previous month.

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The methods section should be presented in the past tense. An example of a common source of error that can lead to data inaccuracy is measurement equipment bias or measurement equipment that is out of calibration.

There are dozens of experimental designs.

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For example, we could calculate the mean and standard deviation of the exam marks for the students and this could provide valuable information about this group of students.

Competencies for Analysis and Applications. For this reason, do not assume that any single experiment can prove a cause-effect relationship. What were the key findings from the data.

In this case, the frequency distribution is simply the distribution and pattern of marks scored by the students from the lowest to the highest. The measuring tools, which consisted of a piece of string and a ruler, were the limiting factors in getting more refined measurements. In Section 4, we'll learn about p.

If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

For a relative frequency histogram: Choose a minimally sufficient statistical procedure; provide a rationale for its use and a reference for it. · In this module, we will focus on visual summarization techniques for quantitative data similar to what we have here.

In this lecture, you learned two graphical methods in summarizing data stylehairmakeupms.com  · Graphical Descriptive Techniques II Summarizing Quantitative Data A common graphical representation of quantitative data is a histogram.

This graphical summary can be prepared for datastylehairmakeupms.com~nosedal/sta/stylehairmakeupms.com  · Historical data can be quantitative, as in census data, for instance, or qualitative, as in diaries.

Historical quantitative data can be analyzed by either tracking trends or comparing cases over time or by identifying or associating distinct patterns in aggregate data stylehairmakeupms.com  · Data accuracy – Apply techniques that ensure data accuracy and integrity, and identify factors that can influence data accuracy such as source/resource issues, flexibility, versatility, inconsistency, inappropriate interpretation of data values, and stylehairmakeupms.com /quantitative-methods-tools/ summarizing-data.

the number of classes should be the smallest whole number K that makes the quantity 2 to the power of K greater than the number of measurements in the data set, ex. with 65 values, 2 to the sixth power =64 and 2 to the seventh power istherefore the number of classes is 7 (K=7)stylehairmakeupms.com  · are some common mathematical techniques that can make your evaluation data more understandable.

Called Analyzing Quantitative Data Ellen Taylor-Powell G Table 1. Frequency distribution of Extension partici- The mean is also useful for summarizing findings from rating scales.

Even with narrative scales, we can assign a stylehairmakeupms.com

2 Data collection techniques Techniques for summarizing quantitative data
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Overview of Quantitative Methods - Center for Innovation in Research and Teaching