Understanding and interpreting the report findings by Hoem Seiha

1. By Hoem Seiha
Director
Tel: +855-12-699-553
Email: hoemseiha@gmail.com

2. Subject Outline
The most challenging task for a novice news reporter is
not being able to well understand and interpret key
statistics, figures, or several other indicators from an
economic or business report. In this session, you will
learn:
 Frequently-used statistics and indicators from a report
 Interpreting the statistics, figures, or indicators from a
report

3. Research Terms
Numerous statistical terms might exist in an economic, industry,
market, or business study report. Key statistical terms that are
frequently used are:
 Survey – it can be both quantitative and qualitative methods
conducting a study by choosing a certain group of samples to
represent the population. This involve small costs.
 Census – Unlike a survey, this study generally involves all the
population in order to generate most accurate data and confidence.
This involves large costs.
 Sample – a sample is a person or any subject to be involved in the
survey. The larger the sample size is, the better it bring about
confidence.
 Sampling – this is the process of selecting samples to be surveyed
for the study

4. Research Terms (Cont. 1)
 Quantitative research/study – this type of study involves
a large scale of study, usually with lots of samples (e.g.
survey with more than 50 samples).
 Qualitative research/study – this involves smaller scale
of study, usually desk study, focus group interviews, or case
studies.
 Findings or Results – this is the indication and show of
what the study or research findings (also called “results”)
have primarily found after the survey and other analyses.

5. Statistical Terms
 Percentage - is a number or ratio expressed as a fraction of 100,
denoted using a sign “%” or “pc” or “pct”.
 Arithmetic Mean (Average, Avg.) - the arithmetic mean of a
set of data is found by taking the sum of the data, and then
dividing the sum by the total number of values in the set. A
mean is commonly referred to as an average.
 Minimum (Min) – Minimum is the smallest number in a data
set (in the whole samples or entire population)
 Maximum (Max) – Maximum is the largest number in a data set
(in the whole samples or entire population)
 Standard Deviation (Std Dev) – A measure that is used to
quantify the amount of variation or dispersion of a set of data
values.

6. Statistical Terms (Cont.)
 Number of Observations (Obs.) – is the total number of subjects to
be measured in a specific calculation.
 Mode – the mode is the number that is repeated most often.
 Quartile – it’s the value that divides a list of numbers into quarters.
 25% of the percentile is the 1st quartile,
 50% of the percentile is the 2nd quartile or median,
 75% of the percentile is the 3rd quartile
 Median – the median is the middle value of a set of data.
 Correlation – Correlation is a statistical technique that can show
whether and how strongly pairs of variables are related. For example,
height and weight are related; taller people tend to be heavier than
shorter people.
 Regression - a measure of the relation between the mean value of one
variable (e.g. output) and corresponding values of other variables (e.g.
time and cost).

7. Example: Percentage
The study of restaurant consumer
market was conducted in the
second quarter of 2014. The study
took 991 sample subjects to
examine the consumer behavior
and attitude of dining and meal
consumptions amongst white-
collar professional population.
See this example of the
percentage of the samples
classified by occupations.

8. Example: Simple Statistics
2014 Land Price (Asking Prices) in Chamkarmon District)
Average (arithmetic mean) $ 2,413
Std Dev $ 1,071
Min $ 1,010
Max $ 6,073
Q1 (1st quartile) $ 1,629
Q2 (also median) $ 2,132
Q3 (3rd quartile) $ 2,904
Obs 72
Source: Land Price Report 2014 by Vtrust Group

9. Coefficient of Determination (R2)
R2 is a statistic that will give some information about the
goodness of fit of a model. In regression, the R2 coefficient of
determination is a statistical measure of how well the regression
line approximates the real data points.
 0.0 (0%, or perfectly negative) = this indicates that the model
explains none of the variability of the response data around its
mean.
 0.5 (50%, or positive) = this indicates that the model explains
some of the variability of the response data scattering around
its mean.
 1 (100%, or perfectly positive) = this indicates that the
model explains all the variability of the response data
around its mean.

10. Example: Coefficient of Determinant (R2)
Interpretation:
Correlation Analysis: Park Café = -0.2; Brown Café = -0.2
• R2 of Park Café = 0.10 (10%) – This means that there is a week positive correlation
between ages of the respondents and their going to Park Café; however, this has a
downward slope, meaning the trend decreases as respondent’s ages increase.
• R2 of Brown Coffee = 0.18 (18%) – There is also a week positive correlation between
ages of respondents and their preference to Brown Café; but this has a downward
slope, meaning that the trend falls as respondents’ ages increase.
R² = 0.1802
R² = 0.1039
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 59 60 65 67 70
Correlation between Customers’ Ages and their Loyalty for the
Selected Restaurants
Brown Coffee & Bakery Park Cafe Linear (Brown Coffee & Bakery) Linear (Park Cafe )

11. Correlation
Correlation can have a value:
 1 is a perfect positive correlation
 0 is no correlation (the values don't seem linked at all)
 -1 is a perfect negative correlation

12. Example: Correlation
R² = 1
R² = 1
0
2
4
6
8
10
12
0 2 4 6 8 10
Correlation of Sleeping Hours and Study Hours
Number of Study hours
Number of Sleeping hours
Linear (Number of Study hours)
Linear (Number of Study hours)
Number of Study
hours
Number of
Sleeping hours
2 10
4 9
6 8
8 7
10 6
Correlation Analysis -1
Interpretation:
There is a perfect negative correlation between the number of study hours and
the number of sleeping hours.

13. Activity #5:
Interpreting and Reporting of Percentage
3%
13%
19%
33%
39%
52%
58%
Reading
newspaper,
etc.
Doing school
assignment
Relaxing Having drink
& snack
Using
computer &
Internet
Discussing on
business or
job
Meeting
friend
Source: Restaurant Consumer Study 2014 by Park Café
Common purposes for going to a coffee shop (Not during
breakfast or lunch time)
Question: (5 minutes)
In a 200-word paragraph, describe the graph given
above and write a paragraph about it so that your
average audience can understand.

14. Activity #6:
Interpreting and Reporting of Radar Graph
0.0%
5.0%
10.0%
15.0%
20.0%
Seminar, Training
Event
Mainstream Media
Seen by getting
across
Heard from
friend(s)
Facebook
Promotional
Materials
Email
SMS
Bought there by
friend(s)
Channels of Brand Awareness (among general respondents)
Santhomuk
Psar Kandal
Vtrust
Question: (5 minutes)
In a 200-word paragraph, describe the graph given above and write a
paragraph about the most interesting findings so that your average
audience can understand.

15. Activity #7:
Interpreting and Reporting of Relationship
Question: (5 minutes)
In a 150-word paragraph, write your interpretation of
the given scatter graph.