Looks like you’ve clipped this slide to already. This allows you to take a deeper look at the units that make up that category. Combining thise research method with quantitative data … For more information on quantitative data analysis, see the following sources: http://archive.gao.gov/t2pbat6/146957.pdf; http://learningstore.uwex.edu/assets/pdfs/G3658-6.pdf. Data Analysis, Presentation and Interpretation of Data, Presentation, analysis and interpretation of data, No public clipboards found for this slide, Energy Department Director at HYDRO CONSTRUCTION & ENGINEERING CO.,LTD. Like correlations, causation can not be inferred from regression. Quantitative data analysis is helpful in evaluation because it provides quantifiable and easy to understand results. Presenter: By using financial research and analysis, quantitative analysis seeks to assess every investment opportunity, as well as try to estimate a change in macroeconomic value. An analysis of variance (ANOVA) is used to determine whether the difference in means (averages) for two groups is statistically significant. Data Analysis Blog. Example: Items measured on a Likert scale – rank your satisfaction on scale of 1-5. Learn more. Nature of quantitative data analysis: To trace, by means of accumulating the relevant data, the influx of refugees from the Caribbean islands to London from 1940 to 1960. However, there are several procedures you can use to determine what narrative your data is telling. A simple summary for introduction to quantitative data analysis. For more information about the quantitative data analysis project please contact: 247458174 or log onto our website: www.datatrackers.com. A frequency distribution is an organized tabulation of the number of individuals or scores located in each category (see the table below). A quantitative data analysis is one which uses the data collected in the analysis to come to inferences which hold true in general as well as in particular instances of the main module on which the analysis is being based. Crosstabs allow you to disaggregate the data across multiple categories. Quantitative Data Analysis Presenter: ASMA MUHAMAD FARHANA BINTI YAAKUB 1 2. Regression is an extension of correlation and is used to determine whether one variable is a predictor of another variable. These include: These types of analyses generally require computer software (e.g., SPSS, SAS, STATA, MINITAB) and a solid understanding of statistics to interpret the results. In this section, you will learn about the most common quantitative analysis procedures that are used in small program evaluation. Tips to keep in mind for World Mental Health Day; Oct. 5, 2020. Due to sample size restrictions, the types of quantitative methods at your disposal are limited. meters or yards). Qualitative research is a better option for exploring participant experiences and opinions. Date of submission of quantitative data analysis: July 2011. From these results it may be inferred that the Boston program is not meeting the needs of its students of color. For example, you might see a strong positive correlation between participation in the summer program and students’ grades the following school year; however, the correlation will not tell you if the summer program is the reason why students’ grades were higher. •The data analysis that can be done depends on the data gathering that was done •Qualitative and quantitative data may be gathered from any of the three main data gathering approaches •Percentages and averages are commonly used in Interaction Design •Mean, median and mode are different kinds of Quantitative data can be analyzed in a variety of different ways. Clipping is a handy way to collect important slides you want to go back to later. In this section, you will learn about the most common quantitative analysis procedures that are … In addition to the basic methods described above there are a variety of more complicated analytical procedures that you can perform with your data. Oct. 8, 2020. Using data from our example, let’s explore the participant demographics (gender and ethnicity) within each program city. This will be compared to the influx of migrants from that region after the commonwealth laws were tightened in the United Kingdom. Find a certified presentation designer for your next project on Prezi Scribd will begin operating the SlideShare business on December 1, 2020 This process will give you a comprehensive picture of what your data looks like and assist you in identifying patterns. Ltd. See our User Agreement and Privacy Policy. The purpose of this quantitative data analysis is to highlight and investigate a movement in history which has not received much attention yet, apart from in literature. Data tabulation (frequency distributions & percent distributions), Mean – the numerical average of scores for a particular variable, Minimum and maximum values – the highest and lowest value for a particular variable, Median – the numerical middle point or score that cuts the distribution in half for a particular variable, Listing the scores in order and counting the number of scores, If the number of scores is odd, the median is the number that splits the distribution, If the number of scores is even, calculate the mean of the middle two scores, Mode – the most common number score or value for a particular variable, A meaningful mean can only be calculated from interval and ratio data, Minimum and maximum values can be calculated for all levels of measurement, A meaningful median can only be calculated from ordinal, interval, and ratio data, The mode can be calculated for all levels of measurement, Females are overrepresented in the New York program, and males are overrepresented in the Boston program, Over 70% of the White sample is in the Boston program while only 14% of the Black sample is represented in that program, Asian and Latino/a participants are evenly distributed across both program cities, The entire Native American sample (n=2) is the Boston program. The first thing you should do with your data is tabulate your results for the different variables in your data set. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. 1. You can change your ad preferences anytime. Name of organization conducting a quantitative data analysis: Data Tracker Pvt. A regression can be used to determine how strong the relationship is between your intervention and your outcome variables. 1. As of this date, Scribd will manage your SlideShare account and any content you may have on SlideShare, and Scribd's General Terms of Use and Privacy Policy will apply. Quantitative analysis is a mathematical and statistical method of studying behavior and predicting certain outcomes that investors use in their decision-making process. A correlation merely indicates that a relationship or pattern exists, but it does not mean that one variable is the cause of the other. The influx of migrants from the Caribbean islands to London was enormous in the said period. Quantitative data can be analyzed in a variety of different ways. Any quantitative data collection method capturing information in numbers, figures, or values and enabling mathematica and statistical analysis is best to conduct the quantitative research. Descriptives Calculated for “Satisfied with Program Experience”. Dissatisfaction by Gender, Race, & Program City. Before you begin your analysis, you must identify the level of measurement associated with the quantitative data. Jamaica particularly saw a huge portion of the community leave its shores for the “motherland”.

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