Standard Research and Analytical Courses€¦ · concepts used in research e.g. randomised controlled trials, cohort studies, longitudinal designs, randomisation etc. Participants

John Varlow Statistics, Analysis and Research: Training and Consultancy

1 | P a g e https://www.johnvarlow.com Prepared January 2020 Tel: 07879 681898

Standard Research and

Analytical Courses

January 2020

http://www.johnvarlow.com/

John Varlow | Training and Consultancy

Standard Research and Analytical Courses January 2020

2 | P a g e https://www.johnvarlow.com

Course Outlines

The courses below have been designed for analysts, managers,

clinicians and others who are interested in research and analytics. They

are listed in a logical order so that learning can transfer across sessions.

Research Topics

An Overview of Research (2 * ½ Day)

Survey / Questionnaire Design (½ Day)

Writing a Research Proposal (½ Day)

An Introduction to Critical Appraisal (½ Day)

Critical Appraisal Skills (1 Day)

An Introduction to Project Management (including Agile) (½ Day)

Analytical Topics

Principles of Analysis: Descriptive and Inferential Statistics (½ Day)

Statistics and Data Insight (1 Day)

An Introduction to Descriptive Statistics (½ Day)

An Introduction to Inferential Statistics (½ Day)

Key Statistical Concepts 1 (1 Day)

Key Statistical Concepts 2 (1 Day)

Statistical Process Control (1 Day)

Regression Methods and Models (1 Day)

An Introduction to Time Series (1 Day)

Time Series and Forecasting (1 Day)

An Introduction to Epidemiological Methods (½ Day)

Epidemiological / Population Methods (1 Day)

Indicator Development (1 Day)

IT Related Topics

Quantitative Analysis using SPSS (2 * ½ Day)

Macros in Microsoft Excel (½ Day)

Power Pivot and Power Query in Microsoft Excel (2 Days)

Quantitative Analysis using Jamovi fronted R (Open Source) (1 Day)





A more detailed description of each course can be found in subsequent

pages (and is the same as on www.johnvarlow.com/courses).

Please note that there are some additional courses available on my

website that have been designed specifically for individual clients. A

bespoke service is therefore available if you cannot find what you need

in this brochure.

Pricing options for standards courses can be found at the end of this

document.


http://www.johnvarlow.com/courses




Research Topics

An Overview of Research

Aims:

• To introduce participants to the variety of research designs and research language.

• To identify and evaluate these designs, exploring both their strengths and weaknesses. To introduce participants to the concepts of professional and scientific knowledge

• To discuss the scientific method, its origins and importance in formulating theories

• To introduce different perspectives on research, namely the positivist and interpretivist paradigms

• To introduce the main research designs, and when they should be used

Content:

The morning session contains activities that will help define many of the designs and concepts used in research e.g. randomised controlled trials, cohort studies, longitudinal designs, randomisation etc. Participants will be required to define and provide advantages and disadvantages for each of these concepts and identify these features within a list of given studies.

In the afternoon session, participants will be introduced to ways of thinking about “research”. Both the positivist and interpretivist paradigms will be explored, and there will also be discussion around the scientific method and its importance in positivist research. Group activities will focus around the research process, research focus and research questions. The session will also introduce participants to the three common research designs.

Duration:

• 1 Day

• (Can also be delivered as 2* 3 hour sessions)

Pre-requisites:

• None


https://www.johnvarlow.com/courses/research#h.p_iJqoCc8aKxAP

https://www.johnvarlow.com/courses/research#h.p_iJqoCc8aKxAP

https://www.johnvarlow.com/courses/research#h.p_aqWOIANFK3mX

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Writing a Research Proposal

Aims:

• To emphasise the importance of the research question

• To identify the aims and objectives of the study, and how they link to the research question

• To discuss the importance of the methodology

• To discuss ethics, and how to address ethical issues

• To discuss resources and timeframes

Content:

Using a combination of formal teaching, and group exercises, participants will be introduced to the importance of writing a research proposal, and the key stages of the research process: including design, sampling, recruitment, data collection, analysis, and project management. Participants will be introduced to research question writing, using the PICO approach. Particular attention will be paid to ethics and rigour in the design and conduct of research.

Duration:

• 3 hours

Pre-requisites:

• None


https://www.johnvarlow.com/courses/research#h.p_y_qJkrW-LMDD

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An Introduction to Critical Appraisal

Aims:

• To illustrate to participants the importance of critically appraising literature as opposed to simply reading the literature

• To introduce the randomised controlled trial and related concepts

• To introduce basic statistical concepts, including p values and confidence intervals

• To formally critically appraise an article

Content:

Based on the Critical Appraisal Skills Programme (CASP) appraisal tool and format- and through facilitated small group work, participants will solve a problem scenario by critically appraising an article in a systematic way. An introduction to relevant statistical principles will be included within this session, including what statistical tests should be expected within research literature, and how they should be interpreted.

Duration:

• 3 Hours (A longer full day session “Critical Appraisal Skills” is also available which covers the statistics within papers in more detail)

Pre-requisites:

• None

PLEASE NOTE: Some pre-reading of a scientific paper will be required for this session


https://www.johnvarlow.com/courses/research#h.p_P1bI1XQUMYkz

https://www.johnvarlow.com/courses/research#h.p_P1bI1XQUMYkz




Critical Appraisal Skills

Aims:

• To illustrate to participants the importance of critically appraising literature as opposed to simply reading the literature

• To equip participants with the necessary skills to find and critically appraise research evidence about effectiveness in order to promote evidence-based practice

• To introduce the randomised controlled trial and related concepts

• To introduce statistical concepts, including p values and confidence intervals

• To introduce statistical tests for two groups

• To introduce the concepts of risk and hazard

• To formally critically appraise an article

Content:

Based on the Critical Appraisal Skills Programme (CASP) appraisal tool and format- and through facilitated small group work, participants will solve a problem scenario by critically appraising an article in a systematic way. An introduction to relevant statistical principles will be included within this session, including what statistical tests should be expected within research literature, and how they should be interpreted.

Duration:

• 1 Day (A shorter half day session “An Introduction to Critical Appraisal” is also available which does not cover statistics in detail)

Pre-requisites:

• None

PLEASE NOTE: Some pre-reading of a scientific paper will be required for this session





Survey and Questionnaire Design

Aims:

• To provide participants with a practical overview of different methodologies and data collection tools

• To provide participants with an awareness of different sampling methods and sample size issues

• To illustrate the key principles of questionnaire design

• To examine potential sources of bias

• To discuss the importance of piloting

• To discuss what makes a good letter of invitation

Content:

Using a combination of formal teaching and group work, participants will be introduced to the different types of survey design. They will be introduced to different sampling methods, alongside sample size issues, and learn about the principles of questionnaire design. They will become able to identify potential sources of bias, and critique existing questionnaires. We will discuss current data collection methods and tools and the issues related to these. By the end of the session they will be able to select the research methodology and data collection method most suitable for a research question.

Duration:

• 3 hours

Pre-requisites:

• None


https://www.johnvarlow.com/courses/research#h.p_t0sEOzLTN5pX

https://www.johnvarlow.com/courses/research#h.p_t0sEOzLTN5pX




Introduction to Project Management

Aims:

• To illustrate the importance of good project management

• To provide an overview of the key stages within the project – feasibility; initiation; live running; closure and review.

• To illustrate the importance of the sponsor, project board, project manager and project team

• To provide an overview of planning required; determining finance and resources; acquiring staff; and identifying potential risks to the project plan and ways of minimising these.

• To provide an overview of project management tools available, including Gantt Charts

• To discuss the differences between 'waterfall' and 'agile' projects

Content:

There will be a particular emphasis on the practicalities of project planning and management, and on learning from experience, from within the NHS and elsewhere. While Prince2, MSP etc are specific project management methodologies, this session will concentrate on the principles behind such methodologies.

Duration:

• 3 hours

Pre-requisites:

• None


https://www.johnvarlow.com/courses/general#h.p_NK_Ov7VtfZ_1

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Analytical Topics

Principles of Analysis: Descriptive and inferential

Statistics

Aims:

• To introduce descriptive statistics including levels of measurement, central tendency and dispersion

• To introduce concepts of rates (Prevalence and Incidence)

• To discuss data presentation methods

• To give a basic introduction to inferential statistics - statistical tests for 2 groups, P values and confidence limits

• To discuss the importance of data quality

• To discuss the principles of statistical process control

Content:

This session gives a high-level overview of analytical methods. Unlike other sessions there is no group activity for participants. Instead the session is delivered in a discursive manner and aims to give a taster of some of the more detailed sessions on offer.

Duration:

• 2 hours

Pre-requisites

• Basic Numeracy


https://www.johnvarlow.com/courses/research#h.p_hZDelW4lOqXA

https://www.johnvarlow.com/courses/research#h.p_hZDelW4lOqXA




(Understanding) Statistics and Data Insight

Aims:

• To assess a research paper for statistical validity

• To understand how we currently use data, how it is used by the media and how it can be misrepresented and misinterpreted

• To look at outcomes and how they are measured including Nominal, ordinal and interval measures

• To discuss measures of central tendency (mean, median, mode)

• To discuss measures of dispersion (Range, IQR, Standard Deviation)

• To introduce percentages, rates and ratios (Prevalence and Incidence)

• To discuss data distributions, and the importance of normality

• To introduce presentation rules including Chart types and their relationship to data types

• To discuss the two major study designs for two groups, Independent measures and Repeated measures

• To identify whether the correct statistical test has been used based on the stated outcome

• To be able to interpret the test results (the role of chance) including P values and Confidence Intervals

• To understand why the study result isn’t the most important statistic, including the role of power, and the importance of the outcome

• To understand the advantages of stratification of data

• To understand standardisation of data - when it’s used, and the difference between direct and indirect standardisation

• To understand the advantages of looking at time series data, including run charts, moving averages and other smoothing methods

• To understand correlations and cause and effect, using scatterplots and the line of best fit (and its relation to simple forecasting)





Content:

This session differs from other statistics courses on offer as it has few exercises and is, instead, content rich. It introduces concepts that are covered in more detail in other courses (including critical appraisal). Consequently, a lot of content is covered in a relatively short time. A research paper will be sent out before the sessions that participant will be asked to read and attempt to interpret the study results. The morning and afternoon sessions will not only introduce participants to data and statistical concepts but will enable them to interpret the results of the paper and draw meaningful conclusions. The morning session will introduce participants to data and how it is commonly used / misused. We will look at how data is measured, and how it can be summarised. We will look at how data is distributed and why this is important to understanding statistical testing. Data presentation methods will also be looked at, describing the correct way of presenting different types of data. Finally, the two key study designs will be introduced.

The afternoon session will introduce the most common statistical tests related to the study designs and data types we have discussed. We will discuss how the role of chance affects results and how to interpret them. We will then look at other ways to present and interpret data, including stratification and standardisation of data, time series data and correlation of variables. Lastly, we will revisit the results tables from our research paper and use what we have learned to interpret the results.

Duration:

• 1 Day

Pre-requisites

• Basic Numeracy PLEASE NOTE: Some pre-reading of a scientific paper will be required for this session





An Introduction to Descriptive Statistics

Aims:

• To present the key concepts of data measurement

• To introduce summary statistics and methods of calculation

• To introduce the concepts of prevalence and incidence

• To outline measures of central tendency and dispersion

• To introduce the 'bell shaped curve' (the normal distribution)

• To investigate methods of data presentation

Content:

Starting from first principles, we will discuss basic methods for summarising data. The session aims to introduce the concepts of central tendency and dispersion in a participative manner, enabling students to calculate such summary statistics themselves. The normal distribution will be introduced, alongside concepts such as skewness and kurtosis. Methods of presenting data will also be introduced, with students gaining insight into the appropriateness(or not) of each technique.

Duration:

• 3 hours

Pre-requisites

• Basic Numeracy

• Use of a calculator (please bring with you)





An Introduction to Inferential Statistics

Aims:

• To introduce the concept of sampling and standard error

• To relate the concept of standard error to that of confidence limits

• To outline the principles behind formulating and testing statistical hypotheses.

• To explore correlations and the principles of association and causation

Content:

Building on the previous introduction to descriptive statistics sessions, participants will be introduced to more detailed statistical methods, and the concepts behind them. Sampling issues will be addressed, in particular how they relate to the underlying population. Students will be given the opportunity to explore these relationships and develop a more detailed understanding of statistical confidence. Statistical hypotheses will be discussed, including here relationship to one-tailed and two-tailed statistical tests. Finally, correlations will be discussed alongside the principles of association and causation. Real data will be used to demonstrate the role of confounding within such associations.

Duration:

• 3 hours

Prerequisites:

• Basic numeracy


• Completion of “Introduction to Descriptive Statistics” session or similar understanding





Key Statistical Concepts 1

Aims:

• To present the key concepts of data measurement

• To introduce summary statistics and methods of calculation

• To introduce the concepts of prevalence and incidence

• To outline measures of central tendency and dispersion

• To introduce the concept of 'degrees of freedom'

• To understand how data is distributed and introduce the 'bell shaped curve' (the normal distribution)

• To investigate methods of data presentation

• To understand the principles behind the Central Limit Theorem

• To introduce the concept of sampling and standard error

• To relate the concept of standard error to that of confidence limits

• To understand statistical confidence (p values and confidence limits), and how to interpret

• To understand and construct one sided and two-sided statistical hypotheses

• To outline the principles behind formulating and testing statistical hypotheses.

• To explore correlations and the principles of association and causation including Pearson, Kendall’s tau and Spearman

Content:

This session will discuss some of the key statistical concepts associated with

descriptive and inferential statistics. It will start from first principles and explore the

different types of data that we collect, and how we can describe it usefully for

ourselves and others. It will explore how we can use our data to infer things about

larger populations and explore the variability in our own data. Concepts of statistical

confidence and certainty will be described.

Duration:

• 1 Day

Pre-requisites:

• None






Key Statistical Concepts 2

Aims:

• To understand how to formulate analytical questions and corresponding hypotheses

• To discuss data considerations, including data quality issues

• To outline different analytical designs (independent vs related samples),

• To introduce the concept of statistical power, and how it relates to sample size.

• To introduce tests for two independent groups (chi-squared, independent samples t-test, Wilcoxon signed ranks)

• To introduce tests for two related groups (McNemar, Paired samples t-test, Mann Whitney U),

• To discuss the concept of homogeneity of variance, and how it can be tested

• To introduce tests for multiple groups (e.g. one-way and two-way Anova, Kruskal-Wallis etc)

Content:

This session will build on the principles discussed in Key Statistical Concepts 1. Statistical testing will be discussed, and the concept of independent samples and repeated measures will be discussed. The importance of the statistical hypothesis will be emphasised, and how it relates to one tailed and two tailed significance.

Duration:

• 1 Day

Pre-requisites:

• Key Statistical Concepts 1 (or similar)

• Microsoft Excel installed on client machine


https://www.johnvarlow.com/courses/analysis#h.p_NbqJrE7vjf7Q

https://www.johnvarlow.com/courses/analysis#h.p_NbqJrE7vjf7Q




Statistical Process Control

Aims:

• To emphasise the importance of understanding your data

• To understand time series data

• To highlight problems with existing visualisation methods

• To understand natural and special cause variation

• To understand different types of process control charts

• To understand rules for 'out of control' processes

• To discuss process capability

Content:

This session will introduce participants to the concepts of statistical process control, what it is and when it can be used effectively. In particular, participants will have the opportunity to bring their own data and produce simple process control charts from first principles.

Duration

• 3 hours

Prerequisites:

• Basic numeracy

• Use of calculator (please bring with you)

• Microsoft Excel installed on client machine (optional)

PLEASE NOTE: This session will be based around count data that the client has brought with them


https://www.johnvarlow.com/courses/analysis#h.p_UBuV1qMk0FC7

https://www.johnvarlow.com/courses/analysis#h.p_UBuV1qMk0FC7




Regression Methods and Models

Aims:

• To understand the difference between independent variables, dependent variables, confounding variables and other influencing variables

• To understand simple correlation methods, including correlation coefficients and R-squared

• To understand 'line of best fit' based on least squares methods

• To understand simple linear regression and resulting equations

• To understand the concepts of autocorrelation and heteroskedasticity, and the importance of looking at residuals

• To understand how non-linear data can be transformed to fit a linear model

• To understand Multiple Linear regression and resulting equations

• To understand the problem of multicollinearity,

• To understand interactions between variables, and how they can be entered into a model

• To understand non-linear Regression methods including Polynomial regression and Piecemeal Regression

• To understand the concept of Logistic regression, the logit and how it relates to linear regression

• To understand exp(B) and odds ratios within logistic regression results, and how these can be transformed into probabilities

• To introduce the concepts of multinomial logistic regression

• To introduce the concepts of ordinal regression

Content:

This session will enable participants to understand the principles behind linear and logistic regression. The different methods will be discussed as well as data limitations. Practical examples of how regression models can be applied will be used, and the potential for using regression techniques as predictive models will be explored.

Duration:

• 1 Day

Pre-requisites:

• Key Statistical Concepts


• IBM SPSS or similar installed on client machine (optional)


https://www.johnvarlow.com/courses/analysis#h.p_Udt-LOfYz7k-

https://www.johnvarlow.com/courses/analysis#h.p_Udt-LOfYz7k-




Introduction to Time Series

Aims:

• To know the areas to consider and clarify before using any time series method

• To be able to set up and use simple forecasting methods

• To be able to use the functions FORECAST and GROWTH within MS Excel

• To understand the limitations of these functions

• To identify whether data has trend and / or seasonality

• To use regression functions in MS Excel to analyse data with seasonality

• To understand the advantages of exponential smoothing models over regression models

• To identify the correct type of exponential smoothing for the data, identifying whether it is an additive or multiplicative model

• To be able to set up and / or use exponential smoothing spreadsheets

• To understand the limitations of any forecast produced, including interpreting confidence intervals when produced

• To understand some of the practical issues with data used for time forecasting

Content:

This session focuses on ETS models and does not cover more complex ARIMA models that are included in the Time Series and Forecasting Course. In this session we will look at how we deal with time related data, and the different types of variation within it. Different methods will be discussed to identify and smooth out the effects of variation, with a view to being able to use data to predict future activity. A particular focus on practical application and the use of MS Excel will be explored, with the main emphasis on ETS models

Duration:

• 1 Day

Pre-requisites:

• Basic knowledge of MS Excel






Time Series and Forecasting

Aims:

• To understand time series data and how it is defined

• To understand the relationship with process control and regression models

• To understand and identify the different elements of time series data including secular trend, cyclical variation, seasonal variation and residual variation.

• To be able to identify the difference between linear and non-linear trends.

• To understand when to transform data.

• To understand the concept of rolling averages, weighting data and smoothing techniques including exponential smoothing.

• To be able to create and use exponential smoothing techniques including those incorporating seasonality

• To understand the difference between additive and multiplicative models

• To understand the importance of stationarity in data for ARIMA models, and to be able to make data stationary

• To know how to interpret ARIMA models and outputs, including auto-correlation and partial auto-correlation functions

• To give an overview of BATS and TBATS models within R.

Content:

This session will look at how we deal with time related data, and the different types of variation within it. Different methods will be discussed to identify and smooth out the effects of variation, with a view to being able to use data to predict future activity. This session will focus on both ETS and ARIMA models

Duration:

• 1 Day

Pre-requisites:

• Knowledge of Regression Methods and Models


• IBM SPSS or similar installed on client machine (optional)


https://www.johnvarlow.com/courses/analysis#h.p_ca_RuUlmH4vG

https://www.johnvarlow.com/courses/analysis#h.p_ca_RuUlmH4vG

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https://www.johnvarlow.com/courses/analysis#h.p_8PFagv7YIOzi




An Introduction to Epidemiological Methods

Aims:

• To understand different study methods, in particular cohort, cross-sectional, and case-control

• To understand the concepts of causation and prevention

• To understand the role of bias, confounding, validity and generalisability

• To understand event rates in different groups

• To understand prevalence and incidence rates

• To understand relative risk and when it can be used

• To understand how risk and relative risk can be misrepresented and misinterpreted

• To understand the concept of odds ratios

• To understand how to calculate relative risk reduction and absolute risk reduction

• To understand stratification and standardisation methods, including direct and indirect

• To understand the concept of numbers needed to treat

Content:

In this session participants will be introduced to epidemiological methods and their application. In addition to learning some simple epidemiological techniques, participants will be able to discuss the relative strengths and weaknesses of different data collection mechanisms and their associated analysis. Methods for understanding large collected samples of data will be explored and methods of presenting will be discussed, including stratification and standardisation methods.

Duration

• 3 Hours

Prerequisites:

• Basic Numeracy




https://www.johnvarlow.com/courses/analysis#h.p_1GZiVn0z0g_6





















Epidemiological / Population Methods

Aims:

• To understand descriptive epidemiological design strategies including Correlational, Case Study, Case Series and Cross-Sectional

• To understand analytical epidemiological design strategies including Case-Control and Cohort

• To understand interventional epidemiological design strategies, specifically randomised controlled trials

• To understand the role of chance (p-values and confidence intervals), bias, confounding and effect modification on study results

• To be able to stratify data to help remove the effect of confounding

• To understand cause-effect relationships and the contribution of strength of association, biological credibility, time sequence and dose-response

• To understand and calculate prevalence and incidence, crude and category specific rates

• To understand and be able to perform standardisation of data – direct and indirect

• To understand Relative Risk and Odds Ratios and their relation to different study designs

• To understand other ratios including Standardise Mortality Ratios, Proportional Mortality Ratios

• To understand and calculate a number of measures of association, including relative risk reduction, attributable risk, absolute risk reduction, numbers needed to treat / harm

• To understand the Chi-Square test and associated p-values

• To be able to calculate confidence intervals for Relative Risk

• To understand the concept of sample size and calculate for a case control study

• To understand statistical power and calculate for a case control study

• To understand the need for screening tests including the nature of disease

• To understand and calculate the Sensitivity, Specificity, Predicted positive and negative values of a screening test

• To understand how optimal sensitivity and specificity can be determined using ROC curves





Content:

In this session participants will be introduced to epidemiological and population methods and their application. The session not only covers the most common epidemiological analysis, but details the different types of epidemiological studies alongside their strengths and weaknesses. Common issues with epidemiological studies will be discussed as well as techniques for overcoming these including stratification and standardisation methods. In addition to learning epidemiological techniques to understand how exposure and disease are associated, participants will be able to perform sample size and power calculations. Finally, the issue of pro-active screening for diseases will be discussed and concepts such as sensitivity and specificity will be introduced as well as methods to calculate and maximise them, including the use of ROC curves.

Duration

• 1 Day

Prerequisites:

• Basic Numeracy, although knowledge of basic statistics would be an advantage




https://www.johnvarlow.com/courses/analysis#h.p_qCI1fCFT8Kwk

https://www.johnvarlow.com/courses/analysis#h.p_qCI1fCFT8Kwk




Indicator Development

Aims:

• To understand the difference between numbers, metrics and indicators

• To understand the principles of good indicators

• To understand the principles of reliability and validity

• To understand the principles of sensitivity and specificity (and related Type I and Type II errors)

• To understand the role of data quality

• To discuss indicator construction, simple and compound measures

• To discuss standardisation methods (direct and indirect), and when they should be used

• To discuss presentation methods and the problems of ranking

• To discuss the concept of gaming and perverse incentives

• To discuss assurance of methods and what help is available

Content:

This session will look at the current state of indicator production within the system, and the related problems of having poorly defined, duplicate indicators. The session will enable participants to understand the role that indicators play and the importance of them being constructed properly and in a transparent manner. The key principles of good indicator development will be discussed, and related techniques for adjusting indicators will be explored. By the end of the session participants will not only know what makes a well-constructed indicator but they will have the knowledge to access help that is available.

Duration

• 1 Day

Prerequisites:

• Basic Numeracy


https://www.johnvarlow.com/courses/general#h.p_Z8dDFMnD2wCh

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IT Related Topics

Quantitative Analysis using SPSS

Aims:

• To enable participants to utilise SPSS in simple database setup and manipulation

• To understand how SPSS can be utilised in analysing quantitative research data.

• To apply statistical principle to data, and perform statistical tests on two groups

• To enable participants to utilise SPSS for more complex data manipulation

• To understand how to write replicable code

• To apply statistical principle to data, and perform statistical tests on three or more groups

• To understand how to perform more complex analysis, including regression methods and time series

Content:

Workshop containing all major elements of using the SPSS package effectively. Please note that I can also offer most of this session using the free software PSPP.

Duration:

• 1 Day (Can also be delivered as 2 * 3 hour sessions)

Prerequisites:

• Completion of Key Statistical Concepts, or similar understanding

• Completion of Regression Methods or similar understanding

• Completion of Time Series and Forecasting, or similar understanding

• IBM SPSS (or PSPP) installed on client machine

• PC Skills – Keyboard and mouse skills


https://www.johnvarlow.com/courses/analysis#h.p_f9tErU6o_yIH


https://www.johnvarlow.com/courses/analysis#h.p_ShqC4rYS0kws

https://www.johnvarlow.com/courses/analysis#h.p_ShqC4rYS0kws




Macros in Excel

Aims:

• To introduce participants to Macros from the in-built menus

• To be able to enable macros within a worksheet

• To understand where different macros can be stored, and the implications for sharing with others

• To understand how to record macros

• To understand the value of absolute and relative references, and how combining them gives more powerful macros

• To understand how to use keyboard shortcuts in macros, and the advantage of this

• To understand how to look at, and resolve errors

• To introduce participants to macros using VBA

• To understand how macros are structured

• To introduce participants to macros and VBA on the web

• To introduce the concept of looping code

• To be able to add control buttons to recorded macros

Content:

Workshop containing all major elements of using macros within Microsoft Excel effectively.

Duration:

• 3 Hours

Prerequisites:

• Knowledge of Microsoft Excel









Power Pivot and Power Query in Microsoft Excel

Aims:

• To understand how to import different data types into Power Query, including SQL

• To introduce the concept of MCODE

• To understand how to use multiple files in Power Query

• To be able to filter data

• To be able to append data

• To understand automatic updates within Power Query

• To understand the key Power Query functions

• To understand the different ways of “loading data”, including pivot table cache

• To understand the concept of recurrency and how to deal with it

• To understand operators (lookup and positional)

• To understand how to merge file (replacing vlookup)

• To understand how to append different file formats

• To understand the concept of unpivoting data

• To introduce the concepts of joins and merges

• To understand grouping functions

• To understand the “data model” and how to build relationships

• To introduce the concept of DAX formulae

Content:

Workshop containing all major elements of using Power Query and Power Pivot with Microsoft Excel.

Duration:

• 2 Days

Prerequisites:

• Knowledge of Microsoft Excel









Quantitative Analysis using Jamovi fronted R (Open

Source)

Aims:

• To enable participants to utilise JAMOVI in simple database / spreadsheet setup and manipulation

• To understand how JAMOVI can be utilised in analysing quantitative research data.

• To apply statistical principle to data, and perform statistical tests on two groups

• To enable participants to utilise add on modules to add functionality to JAMOVI

• To understand how to write replicable code that can be used in R

• To apply statistical principle to data, and perform statistical tests on three or more groups

• To understand how to perform more complex analysis, including regression methods and time series

• To understand how JAMOVI output can be shared with others

Content:

Jamovi is a new “3rd generation” statistical spreadsheet. designed to be easy to use, It is a good alternative to costly statistical products such as SPSS and SAS. It is built on top of the R statistical language, giving access to the best the statistics community has to offer. It is ideal for those trying to learn R but who still like graphical menues and interactions. This workshop covers all the major elements of using the open source Jamovi package effectively.

Duration:

• 1 Day

Prerequisites:

• Completion of Key Statistical Concepts, or similar understanding

• Completion of Regression Methods or similar understanding

• Completion of Time Series and Forecasting, or similar understanding

• Jamovi, R and R Studio installed on client machine








Pricing Options (Prices correct up to 31.3.2020)

There are a number of different options for the pricing of courses. Please pick the option that will be of most benefit to you.

Per attendee:

This option gives a fixed price per individual attendee.

• £150 for half day

• £250 for full day

Per session:

This option gives a fixed price per session (up to 20 attendees):

• £ 800 for half day

• £1500 for full day

Please note that the nature of some sessions means that they will not work with less than 6 attendees. Consequently, courses cannot be run until a minimum number is reached. If you wish a session to be run for more than 20 attendees, please contact me to discuss whether this is possible.

Location

Each of these options can be delivered at your location or at a location near to me. There are different considerations for each of these locations.

My location:

• I will provide drinks ie tea, coffee, water but there will be no lunch provided as standard. I am happy, though, to pre-negotiate an extra fee to ensure that lunch is provided.

• All handouts will be provided to you electronically and delegates will need to bring a paper copy of these with them.

• If a course is computer-based, then the delegate will be expected to bring a laptop. Details of software to install will be provided to you before the session. Delegates will be expected to have installed this software before the session starts

Your location:

• You will be providing the venue and appropriate refreshments

• While not charging for travel time, I will be travelling to most venues by train / taxi. This cost will be expected to be re-imbursed





• Where a course lasts for more than one day, it is your choice whether these run on consecutive days or not. If this (or the logistics of travel) requires me to stay at your location overnight, then this cost will be expected to be re-imbursed.

• If a course is computer based, then you will be expected to provide an appropriate venue with the software already installed before the session starts

More details on pricing and cancellation can be found at https://www.johnvarlow.com/pricing


http://www.johnvarlow.com/pricing




@johnrvarlow

www.linkedin.com/in/jvarlow

www.johnvarlow.com

www.facebook.com/johnvarlowtraining

[email protected]

07879 681898


Documents

Standard Research and Analytical Courses€¦ · concepts used in research e.g. randomised controlled trials, cohort studies, longitudinal designs, randomisation etc. Participants