SPSS For Healthcare And Life Science Assignment Help

IBM SPSS Statistics is assisting healthcare and medical professionals in making better data-driven decisions. SPSS Statistics can assist healthcare organisations in improving the quality of care across the board, from operations to monitoring, drug development to diagnosis. This course is for you if you want to analyse your own data or work in a research team that uses IBM’s SPSS software.
From data import to descriptive statistics, data visualisation, correlation, mean comparison, and categorical variable analysis, this course will familiarise you with the user interface and enable you to perform all of the most common statistical tests. What will you learn from SPSS For Healthcare And Life Science Statistics:
  • Be familiar with the SPSS user interface
  • Be able to import research data
  • Conduct descriptive statistical analysis
  • Create figures, plots, and graphs from data
  • Compare numerical data point values between categorical groups
  • Conduct tests for categorical variables

KEY FEATURE

Data from any Survey Gizmo survey can be easily exported to SPSS for detailed and thorough analysis. SPSS is simple to learn, use, and apply.

Data in SPSS is saved in.SAV format. The majority of this information comes from surveys. This simplifies the process of manipulating, analysing, and pulling data.

SPSS has simple access to data with various variable types. This variable data is simple to comprehend. SPSS makes it simple for researchers to create models.

SPSS also has a unique method for obtaining data from critical data. SPSS features include trend analysis, assumptions, and predictive models.

SPSS For Healthcare And Life Science Assignment Help

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Key Topics

    SPSS For Healthcare And Life Science Assignment Help

    This course will give you the knowledge and skills you need to conduct and understand evidence-based clinical research. From study design, required sample size, selecting the correct statistical test, checking test assumptions, conducting and interpreting statistics, interpretation of effect sizes and P values, to how to best report results for presentation and publication, a practical, comprehensive, step-by-step guide is provided.
    SPSS commands for commonly used statistical analyses in the health care literature are included, such as t-tests, ANOVA, regression, survival analysis, diagnostic and risk statistics, and so on. Furthermore, the most pertinent corresponding output and interpretation are presented, along with clear and concise explanations. Each chapter includes real-world research examples with downloadable data sets. Critical appraisal checklists are also included to assist researchers in systemically evaluating study results. This new edition includes a new chapter on longitudinal data, which uses both repeated measures and mixed models. In addition, all commands and output have been updated to IBM Statistics SPSS 21 and SigmaPlot 13.

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