{"id":139,"date":"2018-12-15T01:32:45","date_gmt":"2018-12-15T01:32:45","guid":{"rendered":"http:\/\/localhost\/researchub\/?page_id=139"},"modified":"2019-12-12T17:19:01","modified_gmt":"2019-12-12T17:19:01","slug":"statistics-course-for-non-statisticians","status":"publish","type":"page","link":"https:\/\/researchub.co.rw\/?page_id=139","title":{"rendered":"Statistics course for non-statisticians"},"content":{"rendered":"
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Course description <\/strong><\/span>
This course is designed for non-statisticians and has relevance to data users especially in the project management domain. It is intended to equip project managers, research users, policymakers, monitoring and evaluation professionals with the ability to understand, interpret and question the validity of the reports done by consultants. It is important for end users to understand key assumptions that underpin statistical methods before deciding which approach to endorsing. <\/span>
The course is a precursor data analysis using software (SPSS & Stata). Research Hub strongly encourages participants to enroll in this course before applying for data analysis. A discount of Rwf 50,000 applies to applicants who enroll for both courses. <\/span>
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Learning objectives <\/strong><\/span>
Participants who have gone through this course are able to;<\/span>
\u2022 Articulate key relevant concepts as used in qualitative research <\/span>
\u2022 Determine sample size for a descriptive research designs<\/span>
\u2022 Identify the appropriate sample statistical designs for a study<\/span>
\u2022 Understand what it takes to generalize findings <\/span>
\u2022 Interpret statistical reports <\/span>
\u2022 Have a relevant understanding of counterfactual evaluation designs <\/span>
\u2022 Tell when to use what statistical test <\/span>
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Who should attend <\/strong><\/span>
\u2022 Monitoring evaluation experts, project managers and all professional who supervise work done by researchers<\/span>
\u2022 Report writers and communication experts tasked to communicate research findings<\/span>
\u2022 Clinical Project Leaders who will be redesigning and evaluating studies<\/span>
Course content.<\/span>
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Day One<\/strong><\/span>
\u2022 Introduction to statistical concepts <\/span>
\u2022 Statistical symbols <\/span>
\u2022 Descriptive versus inferential studies <\/span>
\u2022 Definition and types of survey bias <\/span>
\u2022 Definition and types of sampling techniques (practical)<\/span>
\u2022 Extrapolation and generalization of research findings to the wider population<\/span>
\u2022 Types of data (categorical, continuous ordinal scale)<\/span>
\u2022 Statistical tests <\/span>
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Day 2<\/strong><\/span>
Evaluation design<\/strong> <\/span>
\u2022 Evaluation design concepts (treatment, control dependent &independent variable etc.)<\/span>
\u2022 Randomized control trial (RCT)<\/span>
\u2022 Quasi-experiments<\/span>
\u2022 Propensity score matching <\/span>
\u2022 Cross section studies <\/span>
Analysis <\/strong><\/span>
\u2022 Analysis of variance (ANOVA) <\/span>
\u2022 T-tests<\/span>
\u2022 Frequency <\/span>
\u2022 Correlation coefficient <\/span>
\u2022 Regression analysis <\/span>
\u2022 Assumptions of underpinning inferential analyses<\/span>
\u2022 Data interpretation <\/span>
\u2022 Limitation of quantitative data<\/span>
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Day two <\/strong><\/span>
\u2022 Analysis of variance (ANOVA) <\/span>
\u2022 T-tests<\/span>
\u2022 Frequency <\/span>
\u2022 Correlation coefficient <\/span>
\u2022 Regression analysis <\/span>
\u2022 Assumptions of underpinning inferential analyses<\/span>
\u2022 Data interpretation<\/span>
\u2022 Limitation of quantitative data <\/span>
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Duration<\/strong> (2-day programme and 3 days evening) <\/span>
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Application process<\/strong><\/span>
Interested applicants are encouraged to send filled application form (see attachment) and their latest CVs to info@researchub.co.rw.<\/span><\/p>\n

M\u00e4rz 2016 um 13 32 ups, ich wollte schreiben ich habe keine kenntnis \u00fcber nrw antworten hinterlasse einen kommentar antwort abbrechen deine e-mail-adresse wird nicht ver\u00f6ffentlicht.<\/span>