Foundation Skills in Data Analysis

Running head: FOUNDATION SKILLS IN DATA ANALYSIS 1
Foundation skills in data analysis
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FOUNDATION SKILLS IN DATA ANALYSIS 2
Foundation skills in data analysis
Various scholars have acknowledged the use of charts, tables, and graphs in analysing and
presenting different sets of statistical data (Robbins, 2012). However, the ease of understanding
the information is entirely reliant on the visualisation skills portrayed in the report (Ware, 2012).
Achieving sufficient visualisation of the data when using tools such as charts, graphs, and tables
is made through various set standards or criteria that can govern the development of the charts as
discussed in the sections below.
Part A: Developing Generic Evaluation Standards
Common evaluation standards for charts, tables, and graphs
1) The charts, tables, and graphs should have titles as well as be numbered using appropriate
indices. Titles give an overview of the entire information being analysed or presented (Boers,
2018).
2) The numerical data should have a similar number of significant figures for all the entries or
rounded off to the same number of decimal places for uniformity.
3) Axes should be well labelled with representative variables along the x- and x-axis indicated
as well as the units of measurements for standardised units.
4) The logical presentation of the data should be observed in the charts, tables, and graphs either
alphabetical or based on the chronological occurrence of events (Collazo, Goergen, & Smith,
2018). This could entail the yearly, monthly, or weekly arrangement of events.
5) The sources should accompany the use of the charts, tables and graphs if they are not
generated from raw data. Sources act as a reference that makes the reader authenticate the
information.

FOUNDATION SKILLS IN DATA ANALYSIS 3
6) Using abbreviations, short forms, or codes in the graphs, tables, and charts should be
illustrated to give meaning. Adding explanation reduces potential confusion of the data.
Evaluation standard for Graphs
7) Using a bar or grouped graphs should have a common baseline upon which all the variables
originate.
8) Graphs with multiple variables under investigation should have a legend for distinguishing
the different variables. Use of legends facilitates faster understanding of the data.
9) Using grouped charts with several variables should entail independent assigning of group
names with distinct features that enables tracing of a single variable across the groups. Use of
colour codes for the variables would ensure the distinguishing of variables among the groups
(Borkin et al., 2013).
10) Simple and common scales should be applied to grouped graphs or those with multiple for
uniformity and faster judgment to the data being analysed or presented.
Evaluation standard for Tables
11) Using tables should be accompanied with appropriate labelling of the rows at the top of the
table or the columns on the left side of the table (Gelman, 2011).
12) The columns and rows in the charts should be separated using gridlines or using sufficient
spacing between the entries. Grids or larger spaces between the entries makes the reader trace
elements or entries with ease.
13) The information or data in tables should be simplified and categorised. Streamlining data
eliminates repetition thus avoiding data redundancies during the presentation.
14) Using long tables that extend to the next layout should have the labels of the rows and
columns at the beginning of every layout/ page as well as the title.

FOUNDATION SKILLS IN DATA ANALYSIS 4
15) The cells that have no data entries should not be left blank. Use of abbreviation such “NA” or
other means such a dash (-) which should be explained in the legend or the table key.
Evaluation standards for Charts
16) Using line charts that have many variables should be evaluated using different trend lines.
The trend lines could be of different colours, thickness, dashed, or continuous for fast
isolation.
17) The time series data or information should be presented using line charts whereby the x-axis
to indicate the time (years, months, weeks, days, hours) while the y-axis to depict the
variable under investigation.
18) Pie charts should be used to represent portions of dependent variables of data expressed as
percentages for quantification purposes. Colour codes for different parts contribute to a more
natural distinction among variables.
19) Line charts should be used to analyse data or represent information that has multiple
dependent variables aligned on the y-axis with a single independent variable aligned along
the x-axis.
20) Line charts should be used for forecasting and predicting the outcomes of a time series data.