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BASIC DATA ANALYSIS (WITH EXCEL) AND DATA INTERPRETATION

BASIC DATA ANALYSIS (WITH EXCEL) AND DATA INTERPRETATION. Basic tools : frequency, cross-tabs, mean, median, share and rate. Frequencies. What? The number of times a certain value or class of values occurs What for? A way to summarise data. Frequencies.

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BASIC DATA ANALYSIS (WITH EXCEL) AND DATA INTERPRETATION

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  1. BASIC DATA ANALYSIS (WITH EXCEL) AND DATA INTERPRETATION

  2. Basic tools: frequency, cross-tabs, mean, median, share and rate

  3. Frequencies What? The number of times a certain value or class of values occurs What for? A way to summarise data

  4. Frequencies Example: Number of students by ISCED level in Italy, 2008 Source: Eurostat

  5. 2,013,856 =0.18 11,165,737 Relative Frequencies (proportions) Example:Number of students by ISCED level in Italy, 2008 Source: Eurostat 18% of students in Italy attended higher education (ISCED 5 and 6) in 2008

  6. + 0.16 =0.56 0.40 Cumulative Frequencies Example:Number of students by ISCED level in Italy, 2008 Source: Eurostat

  7. Cross-tabulations • Used to analyse categorical data (gender, level of education etc.) • Two (or more) dimensional table that records the number (frequency) of respondents that have the specific characteristics described in the cells of the table.

  8. Mean What? Sum of all the values divided by the number of values (arithmetic average), applying to quantitative variables What for? To summarise data and compare them Disadvantage Mean is affected by extreme values (e.g. income variables)

  9. Median What? The midpoint of the data after being ranked (or the average of the two middle numbers in case of the total is even). Thus, there are as many numbers below the median as above the median. What for? To summarise data and compare them Advantage Median is not affected by extreme values

  10. Mean and Median Mean: 54,600 EUR Median: 20,000 EUR Example:Individual salary per year

  11. Rate vs. Share What? A ratio between two measurements, which can be expressed, for example, as a percentage. Where is the difference?See examples

  12. Example: Employment rates by educational attainment (15-64, %) in Italy, 2009 Definition Employment rates represent persons in employment (with a certain level of education) as a percentage of the population of working age (15- 64 years) (with a certain level of education).

  13. Example: The shares (distribution) of the employed population by educational attainment (%) in Italy, 2009 Definition The distribution (shares) of the employed population by educational level represents persons in employment with a certain level of education as a percentage of the total employed population.

  14. Cross-country comparison Example: Country A Total unemployed: 1,000 Labour force (female): 10,000 • Unemployed (female) 800 • Employed (female) 9,200 Country B Total unemployed: 1,000 Labour force (female): 1,600 • Unemployed (female) 800 • Employed (female) 800 Share of the unemployed female (out of total unemployed): Country A: 800/1000 = 80% Country B: 800/1000 = 80% Female unemployment rate (a ratio between the unemployed female and female labour force): Country A: 800/10,000 = 8% Country B: 800/1,600 = 50%

  15. BASIC DATA INTERPRETATION: EXAMPLES

  16. Example 1

  17. Example 1 Interpretation In the first example, we are looking at the question regarding the choice of language applied to a questionnaire. We see that in this hypothetical example there are 8 respondents, but only 7 replied to this question and 1 did not. The graph shows the distribution of responses of the 7 respondents that replied to the question. We can say that 28.57% of respondents chose Kyrgyz language as the language for the questionnaire and 71.43% of respondents chose Russian language as the language for the questionnaire.

  18. Example 2

  19. Example 2 Interpretation In the second example, we are looking at the question “Do you work at this moment?”. We see that in this hypothetical example there are 8 respondents, but only 6 replied to this question and 2 did not. The graph shows the distribution of responses of the 6 respondents that replied to the question. We can say that 16.67% (that is 1 person) of respondents worked at the moment of the interview, 33.33% (that is 2 people) of the 6 respondents did not work and searched for work at the same time. Finally, 50% of respondents (that is 3 people) did not work and did not look for a job at the time of the interview).

  20. Example 3

  21. Example 3 Interpretation Here we analyse the question on the choice of the profession. It was a multiple answer question. Therefore, respondents could tick more than one answer. Here, we see that out of 8 respondents, 6 replied to this question. Out of these six, 83.33% chose the profession because of personal interest. Moreover, 16.67% of the six respondents declared that it was (also) the choice of their parents etc.

  22. Example 4

  23. Example 4 Interpretation: This example deals with a cross-tabulation (i.e. we are taking into consideration two variables at the same time – gender and the current employment situation). In the table and graph we can see that in this hypothetical example, there are 2 women and 3 men. 50% of women (i.e. 1 person) did not work at the moment of interview, but were looking for work. Another 50% of women (i.e. 1 person) did not work and did not look for work at the same time. In case of men, 33.3% of them worked (i.e. 1 out of 3 male respondents), 33.3% of male respondents did not work but searched for employment and another 33.3% of male respondents did not work and did not look for a job.

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