Data Analysis

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    1. Data Analysis

    Data analysis for quantitative research is one of the most common areas. In other words, the main aim of this analysis is to create models and understand the data. Also, analyzing data is a key factor in the decision-making process.

    2. What Is Data Analysis?

    In general, data analysis is about collecting, transforming, and modeling the data. In this process, we follow different methods. For example, we use descriptive data analysis in social sciences. On the other hand, data mining is a statistical model-based analysis technique. Accordingly, we can list the three main areas as follows.

    • Descriptive statistics (DS)
    • Exploratory data analysis (EDA)
    • Confirmatory data analysis (CDA)

    Firstly, descriptive statistics is a quantitative method to describe a set of data. Secondly, Exploratory data analysis generally adopts visual methods to analyze the main properties of a data set. Finally, confirmatory data analysis is about hypothesis testing by random data collection.

    3. Data Analysis Process

    There are 5 main steps for the data analysis process.

    1. Data collection: In this step, we decide the suitable population and sample size. Then, the data collection method depends on the sample size as well as the research topic.
    2. Data processing: This is where the structured data is created. The structured data is necessary for the analysis.
    3. Data cleaning: After data processing, we determine incomplete or duplicate data.  We have to clean the data to obtain reliable results.
    4. Data analysis: We apply one of the methods: DS, EDA, or CDA methods.
    5. Modeling and visualization: The last step is about interpreting and presenting the data. Here, it is possible to plot graphs or charts to show the findings.

    3. Data Analysis Tools

    We can use the following tools for Data analysis Help:

    • IBM SPSS (IBM Statistical Package for Social Science)
    • STATA
    • Matlab
    • Excel
    • Minitab
    • AMOS
    • BI tools (Business Intelligence Tools)
    • R programming
    • Python
    • SQL Consoles
    • SAS Forecasting
    • Rapidminer

    The selection of these tools depends on the data usage purpose. While Excel and IBM SPSS can be ideal for most cases, other data analysis help tools might work better for specific cases.

    4. How OnlineSPSS Helps in Data Analysis?

    1. Submit Your Statistic Project

    Start by clicking on GET INSTANT QUOTE button, enter the required details, and upload supporting files to submit your assignment through our user-friendly order form.

    2. Make the Payment by Paypal

    Our professional experts will review and update the quote for your assignment. Make the payment to start the processing, we have PayPal integration which is quick and secure.

    3. Get Solution

    Just Relax! You will receive a high-quality result that is 100% plagiarism-free within the promised deadline. The Statistical Analysis Report after completion will be sent to your e-mail ID as per the agreed deadline.

    Frequently Asked Questions

    To place the order for your data analysis help with us, you can simply navigate to the Submit Form available on our home page or click the following link: https://www.onlinespss.com/submit-your-project

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    Finally, sit back and relax.

    We have a large pool of Statisticians and each one of them is selected via a rigorous procedure. All of our tutors have gained a master’s or Ph.D. degree and significant writing experience in the statistic field.  Our in-house team carefully selects an expert for your data analysis help.

    We charge the lowest prices in the entire industry. Our service price depends upon your data analysis help specifications and requirements. In conclusion, it is based on the following factors: Content type, Deadline, Discounts and Bonuses, Extra services.

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