Understanding and interpreting the report findings
15
-
Upload
hoem-seiha -
Category
Education
-
view
357 -
download
2
Transcript of Understanding and interpreting the report findings
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
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
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.
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.
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).
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.
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
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.
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 )
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
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.
Activity #5: Interpreting and Reporting of Percentage
3% 13%
19%
33% 39%
52% 58%
Readingnewspaper,
etc.
Doing schoolassignment
Relaxing Having drink& snack
Usingcomputer &
Internet
Discussing onbusiness or
job
Meetingfriend
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.
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)
FacebookPromotional
Materials
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.
Activity #7: Interpreting and Reporting of Relationship
Question: (5 minutes) In a 150-word paragraph, write your interpretation of the given scatter graph.
