which one of the following tools is used for analyzing data?
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Data Analysis Tools, Charts, and Diagrams Use the following tools to collect or analyze data: Box and whisker plot: A tool used to display and analyze multiple sets of variation data on a single graph. ... Survey: Data collected from targeted groups of people about their opinions, behavior or knowledge.
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['Analysis of variance (ANOVA)', 'Chi-squared test.', 'Correlation.', 'Factor analysis.', 'Mann–Whitney U.', 'Mean square weighted deviation (MSWD)', 'Pearson product-moment correlation coefficient.', 'Regression analysis.']
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Best Text Mining Tools of 2020. ... Equipped with Natural Language Processing (NLP), text mining tools are used to analyze all types of text, from survey responses and emails to tweets and product reviews, helping businesses gain insights and make data-based decisions.
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['Document analysis.', 'Surveys.', 'Interviews.', 'Observations.', 'Focus groups.', 'Case studies.']
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Data collection is simply the process of getting (gathering) data from people (sample) while data analysis is the process of gaining useful insight from collected data.
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Data analysis is important in business to understand problems facing an organisation, and to explore data in meaningful ways. Data in itself is merely facts and figures. Data analysis organises, interprets, structures and presents the data into useful information that provides context for the data.
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Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation).
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['Scatter plot. Scatter plots present data on the x- and y-axes and are used to investigate an association between two variables. ... ', 'Bar graph and histogram. ... ', 'Pie chart. ... ', 'Box and whisker chart. ... ', 'Three-dimensional effects. ... ', 'Drawing a graph: example.']
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Regression analysis is a powerful statistical method that allows you to examine the relationship between two or more variables of interest. While there are many types of regression analysis, at their core they all examine the influence of one or more independent variables on a dependent variable.
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Statistical analysis software, such as SPSS, is often used to analyze quantitative data. Qualitative data describes qualities or characteristics. ... Coding allows the researcher to categorize qualitative data to identify themes that correspond with the research questions and to perform quantitative analysis.
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Cause analysis tools are helpful tools for conducting a root cause analysis for a problem or situation. They include: Fishbone diagram: Identifies many possible causes for an effect or problem and sorts ideas into useful categories.
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Most are based around a core set of basic tools. These include interviews, focus group discussions, observation, photography, video, surveys, questionnaires and case studies. Data may also be generated through direct measurement, reviewing secondary data, and informal project / programme management processes.
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['Comparison of Top Data Analytics Tools.', '#1) Microsoft BI.', '#2) HubSpot.', '#3) Tableau Public.', '#4) RapidMiner.', '#5) KNIME.', '#6) Orange.', '#7) OpenRefine.']
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The most commonly used data analysis methods are: Content analysis: This is one of the most common methods to analyze qualitative data. ... Narrative analysis: This method is used to analyze content from various sources, such as interviews of respondents, observations from the field, or surveys.
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['Flowchart. Most of us are familiar with flowcharts. ... ', 'Check Sheet. A check sheet is a basic quality tool that is used to collect data. ... ', 'Cause and Effect (fish bone) Diagram. ... ', 'Pareto Chart. ... ', 'Control Charts. ... ', 'Histograms. ... ', 'Scatter Diagrams.']
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Data collection is the systematic recording of information; data analysis involves working to uncover patterns and trends in datasets; data interpretation involves explaining those patterns and trends.
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Data collection is gathering of information from various sources, and data analytics is to process them for getting useful insights from it. ... For data collected from different sources and methods need specific data analysis methods and tools to process and get insights from them.