Quantitative analysis techniques
Learn techniques to get more rich, useful information out of your data using excel, and take the next step to build a rich profile of data-driven marketing a spreadsheet opened in front of you, you stare at mountains of raw data without a clue what to do, feeling like you’re drowning in the ’ve heard marketers talking about data-driven marketing and “big data,” and having learned that many companies such as facebook are using third party data, you sent out surveys and collected tons of data in order to do some of that “data-driven marketing” you’ve heard so much about. In this blog post, i will introduce to you the seven most common and useful data analysis techniques for survey analysis, and then walk you through their processes in excel. Note: the following examples will be shown in excel analysis technique 1: frequency distribution (histogram in excel). Distribution is a simple data analysis technique which allows you to get a big picture of the data. This technique will be introduced analysis technique 2: descriptive the frequency distribution we can figure out the frequency of the values observed, as shown in the “age example” above. Click “summary statistics” output will look like this:From this, you can easily learn about the central tendency and dispersion of the values for the analysis technique 3: comparing means – statistical up! The way to do a two-sample t-test is similar to the paired t-test, except that you need to choose “ttest: twosample assuming unequal variances” in the tool analysis technique 4: cross-tabulation (pivot table in excel). Tabulation, also called pivot table in excel, is one of the most popular techniques for data analysis. Analysis technique 5: ations are used when you want to know about the relationship between two variables.
Click in the box next to “array 2” and highlight the second column of analysis technique 6: linear sion is a more accurate way to test the relationship between the variables compared with correlations since it shows the goodness of fit (adjusted r square) and the statistical testing for the variables. To do regression analysis in excel:I use the example of a multiple regression of ratings for product quality and ratings for packaging on the willingness to pay. Therefore, when making marketing decision, marketers should focus on the product quality according to this survey analysis technique 7: text the survey, there are always some open questions which will allow respondents to fill in their own answers. In this example, it indicates the respondents’ job titles are related to marketing, manager, seo and director, learning these techniques for data analysis, i bet you won’t feel like drowning any more when looking into the spreadsheet with tons of are some useful resources for data analysis techniques:Computer help : how to make a pivot table in spss for t uction to regression analysis with excel. Just what i was looking for to gain some insight on data analysis techniques for my research. Am working as a sr engineer quality assurance for pricol technologies,i have interest in data analysis,how can my make my career more effective. If you are a beginner of data analysis, i will recommend you learn and practice the techniques in this post and learn more about advanced excel skills. When you become more advanced in data analysis, you can learn sql or sas, with what you can deal with bigger datasets. Such a useful and very interesting stuff to do in every research and data analysis you wanna do!
Thank you very much for the very organized data analysis tips i learned a lot from it. But things can’t learn easily i will need few more attempts and patience to master this kanth adepu says:July 15, 2014 at 9:52 jiafeng li, thanks for this info about data analysis techniques. I am alergic to data, but i need to write some exams on quantitative analysis, reason why i am on this anrao, says:June 13, 2015 at 10:08 analysers ask:how to compute adjusted r is the use of paired t we always assume unequal variances for t 3, 2015 at 10:51 useful article for me as monitoring and evaluation by authorrelated postspopular play games on smartphones more often than men ts off on women play games on smartphones more often than men do – infographic. Seo analysis : online shopping behavior in the digital : the secret to successful marketing ts off on mart: the secret to successful marketing alone won’t guarantee better marketing ts off on data alone won’t guarantee better marketing persona-driven keyword research play games on smartphones more often than men ts off on women play games on smartphones more often than men do – most powerful competitor research tool you’re not using (yet). Analysis refers to economic, business or financial analysis that aims to understand or predict behavior or events through the use of mathematical measurements and calculations, statistical modeling and research. Quantitative analysis is employed for a number of reasons, including measurement, performance evaluation or valuation of a financial instrument, and predicting real world events such as changes in a country's gross domestic product (gdp) growth ng down 'quantitative analysis'. General terms, quantitative analysis can best be understood as simply a way of measuring or evaluating things through the examination of mathematical values of variables. The primary advantage of quantitative analysis is that it involves studying precise, definitive values that can easily be compared with each other, such as a company's year-over-year revenues or earnings. In the financial world, analysts who rely strictly on quantitative analysis are frequently referred to as "quants" or "quant jockeys.
Governments and central banks commonly track and evaluate statistical data such as gdp and employment uses of quantitative analysis in investing include the calculation and evaluation of key financial ratios such as the price-earnings ratio (p/e) or earnings per share (eps). Quantitative analysis ranges from examination of simple statistical data such as revenue, to complex calculations such as discounted cash flow or option tative vs. Qualitative quantitative analysis serves as a very useful evaluation tool by itself, it is often combined with the complementary research and evaluation tool of qualitative analysis. For example, it is easy for a company to use quantitative analysis to evaluate figures such as sales revenue, profit margins or return on assets (roa), but the company may also wish to evaluate information that is not easily reducible to mathematical values, such as its brand reputation or internal employee a combined qualitative and quantitative analysis project, a company, analyst or investor might wish to evaluate the strength of a particular product that a company manufactures and sells. The qualitative analysis part of the project can be undertaken using tools such as customer surveys that ask consumers for their opinions about the product. A quantitative analysis of the product can also be initiated through the examination of data regarding numbers of repeat customers, customer complaints and the number of warranty claims over a given period of on analysis - t with with with investopedia. Types of learning tanding your preferences to aid al thinking al thinking and fake g a dissertation or uction to research tative and qualitative research ative research iews for ative data from tative research ng and sample s and survey ational research and secondary ing research ing qualitative statistical tical analysis: identifying ariate our new research methods of the skills you need guide for ng, coaching, mentoring and ability skills for ibe to our free newsletter and start improving your life in just 5 minutes a 'll get our 5 free 'one minute life skills' and our weekly 'll never share your email address and you can unsubscribe at any tative and qualitative research also: surveys and survey ch methods are split broadly into quantitative and qualitative you choose will depend on your research questions, your underlying philosophy of research, and your preferences and pages introduction to research methods and designing research set out some of the issues about the underlying page provides an introduction to the broad principles of qualitative and quantitative research methods, and the advantages and disadvantages of each in particular tative research is “explaining phenomena by collecting numerical data that are analysed using mathematically based methods (in particular statistics). If there are no numbers involved, then it’s not quantitative phenomena obviously lend themselves to quantitative analysis because they are already available as numbers. However, even phenomena that are not obviously numerical in nature can be examined using quantitative e: turning opinions into you wish to carry out statistical analysis of the opinions of a group of people about a particular issue or element of their lives, you can ask them to express their relative agreement with statements and answer on a five- or seven-point scale, where 1 is strongly disagree, 2 is disagree, 3 is neutral, 4 is agree and 5 is strongly agree (the seven-point scale also has slightly agree/disagree).
Scales are called likert scales, and enable statements of opinion to be directly translated into numerical development of likert scales and similar techniques mean that most phenomena can be studied using quantitative is particularly useful if you are in an environment where numbers are highly valued and numerical data is considered the ‘gold standard’. It is important to note that quantitative methods are not necessarily the most suitable methods for investigation. It is also possible that assigning numbers to fairly abstract constructs such as personal opinions risks making them spuriously s of quantitative most common sources of quantitative data include:Surveys, whether conducted online, by phone or in person. Which may either involve counting the number of times that a particular phenomenon occurs, such as how often a particular word is used in interviews, or coding observational data to translate it into numbers; ary data, such as company pages on survey design and observational research provide more information about these ing quantitative are a wide range of statistical techniques available to analyse quantitative data, from simple graphs to show the data through tests of correlations between two or more items, to statistical significance. Other techniques include cluster analysis, useful for identifying relationships between groups of subjects where there is no obvious hypothesis, and hypothesis testing, to identify whether there are genuine differences between page statistical analysis provides more information about some of the simpler statistical ative research is any which does not involve numbers or numerical often involves words or language, but may also use pictures or photographs and any phenomenon can be examined in a qualitative way, and it is often the preferred method of investigation in the uk and the rest of europe; us studies tend to use quantitative methods, although this distinction is by no means ative analysis results in rich data that gives an in-depth picture and it is particularly useful for exploring how and why things have r, there are some pitfalls to qualitative research, such as:If respondents do not see a value for them in the research, they may provide inaccurate or false information. See our page on reflective practice for s of qualitative gh qualitative data is much more general than quantitative, there are still a number of common techniques for gathering it. The best way to work out which ones are right for your research is to discuss it with academic colleagues and your page analysing qualitative data provides more information about some of the most common y, it is important to say that there is no right and wrong answer to which methods you mes you may wish to use one single method, whether quantitative or qualitative, and sometimes you may want to use several, whether all one type or a mixture. It is your research and only you can decide which methods will suit both your research questions and your skills, even though you may wish to seek advice from ng and sample iews for g a research proposal | writing a ing qualitative data | simple statistical @tative analysis (chemistry). Analytical chemistry, quantitative analysis is the determination of the absolute or relative abundance (often expressed as a concentration) of one, several or all particular substance(s) present in a sample.
Knowing the composition of a sample is very important, and several ways have been developed to make it possible, like gravimetric[2] and volumetric analysis. Gravimetric analysis yields more accurate data about the composition of a sample than volumetric analysis but also takes more time to perform in the laboratory. Volumetric analysis, on the other hand, doesn't take that much time and can produce satisfactory results. Volumetric analysis can be simply a titration based in a neutralization reaction but it can also be a precipitation or a complex forming reaction as well as a titration based in a redox reaction. However, each method in quantitative analysis has a general specification, in neutralization reactions, for example, the reaction that occurs is between an acid and a base, which yields a salt and water, hence the name neutralization. In the redox titration that reaction is carried out between an oxidizing agent and a reduction example, quantitative analysis performed by mass spectrometry on biological samples can determine, by the relative abundance ratio of specific proteins, indications of certain diseases, like tative vs. Quantitative analysis refers to analyses in which the amount or concentration of an analyte may be determined (estimated) and expressed as a numerical value in appropriate units. Qualitative analysis may take place with quantitative analysis, but quantitative analysis requires the identification (qualification) of the analyte for which numerical estimates are given. Term "quantitative analysis" is often used in comparison (or contrast) with "qualitative analysis", which seeks information about the identity or form of substance present.
He or she will use "qualitative" techniques (perhaps nmr or ir spectroscopy) to identify the compounds present, and then quantitative techniques to determine the amount of each compound in the sample. Careful procedures for recognizing the presence of different metal ions have been developed, although they have largely been replaced by modern instruments; these are collectively known as qualitative inorganic analysis. Similar tests for identifying organic compounds (by testing for different functional groups) are also techniques can be used for either qualitative or quantitative measurements. It could also be used as a quantitative test, by studying the color of the indicator solution with different concentrations of the metal ion.