SPSS Multiple Regression Analysis Expert
Budget: $250 – $750 AUD
I am currently seeking an experienced data analyst who is proficient in SPSS to help with a moderation multiple regression analysis project. The main goal of this project is to evaluate the influence of several components on a dependent variable.
The ideal candidate for this job would have:
• An excellent understanding of SPSS software
• Knowledge in moderation multiple regression analysis
• Proven experience working with CSV file databases
For the tasks at hand, a CSV file generated from an external survey will serve as the primary data source. Thus, the successful candidate should be comfortable handling this format of data and extracting insights from it.
Please, when placing a bid, provide evidence of similar projects you've worked on in the past. I look forward to your proposals.
for the
The Results section of a Moderation multiple regression Analysis describing and summarises the data obtained and the outcomes of analyses performed.
For quantitative research model include the presentation of (a) data cleaning, (b) assumption checking, (c) preliminary analyses (descriptive statistics), and (d) inferential statistics (i.e., hypothesis testing including, if relevant, post-hoc analyses). Data should be presented in relation to hypotheses, but not interpreted.
Data Cleaning
, and any steps taken to confirm the integrity of the data (e.g., screening for errors) and prepare it for analysis (e.g., calculation of variables). This section also includes statistical analysis and decisions around missing data.
Assumption Checking
Each hypothesis model being tested will have a set of assumptions which need to be assessed to ensure that the final results obtained are robust and can be appropriately interpreted. These may involve univariate and multivariate assumptions.
When you introduce your assumptions, please include the statistical approach and model which they relate to so that the reader knows which model is being tested and if it has been done correctly (e.g., "Prior to testing the hypothesis that age will moderate the relationship between grandiose narcissism and maladaptive perfectionism, the assumptions relevant to multiple regression analysis were examined.").
Preliminary Analyses (Descriptive Statistics)
These statistics provide an overview of the variables used in your subsequent analyses. It may include descriptions of each primary and secondary outcome, including the total sample and each subgroup or be presented according to variable. It often includes the number of cases, cell means, standard deviations, and other measures (if appropriate) that characterize the data.
Inferential Statistics
These statistics are used to test your hypothesis/es, specifically by obtaining a sample and “inferring” the results to the population of interest. Each inferential statistic (e.g., moderation, MANOVA, multiple regression) have their own presentation style in terms of the statistics that need to be reported, so it is important that these are well-researched and included where possible. Furthermore, in addition to the p-statistic, other measures of significance (e.g., effect sizes and confidence intervals) should also be presented.
please contact me to obtain data set and DAP
The ideal candidate for this job would have:
• An excellent understanding of SPSS software
• Knowledge in moderation multiple regression analysis
• Proven experience working with CSV file databases
For the tasks at hand, a CSV file generated from an external survey will serve as the primary data source. Thus, the successful candidate should be comfortable handling this format of data and extracting insights from it.
Please, when placing a bid, provide evidence of similar projects you've worked on in the past. I look forward to your proposals.
for the
The Results section of a Moderation multiple regression Analysis describing and summarises the data obtained and the outcomes of analyses performed.
For quantitative research model include the presentation of (a) data cleaning, (b) assumption checking, (c) preliminary analyses (descriptive statistics), and (d) inferential statistics (i.e., hypothesis testing including, if relevant, post-hoc analyses). Data should be presented in relation to hypotheses, but not interpreted.
Data Cleaning
, and any steps taken to confirm the integrity of the data (e.g., screening for errors) and prepare it for analysis (e.g., calculation of variables). This section also includes statistical analysis and decisions around missing data.
Assumption Checking
Each hypothesis model being tested will have a set of assumptions which need to be assessed to ensure that the final results obtained are robust and can be appropriately interpreted. These may involve univariate and multivariate assumptions.
When you introduce your assumptions, please include the statistical approach and model which they relate to so that the reader knows which model is being tested and if it has been done correctly (e.g., "Prior to testing the hypothesis that age will moderate the relationship between grandiose narcissism and maladaptive perfectionism, the assumptions relevant to multiple regression analysis were examined.").
Preliminary Analyses (Descriptive Statistics)
These statistics provide an overview of the variables used in your subsequent analyses. It may include descriptions of each primary and secondary outcome, including the total sample and each subgroup or be presented according to variable. It often includes the number of cases, cell means, standard deviations, and other measures (if appropriate) that characterize the data.
Inferential Statistics
These statistics are used to test your hypothesis/es, specifically by obtaining a sample and “inferring” the results to the population of interest. Each inferential statistic (e.g., moderation, MANOVA, multiple regression) have their own presentation style in terms of the statistics that need to be reported, so it is important that these are well-researched and included where possible. Furthermore, in addition to the p-statistic, other measures of significance (e.g., effect sizes and confidence intervals) should also be presented.
please contact me to obtain data set and DAP