W9

Question 1

Content analysis

Answer 1

quantitative, systematic and objective technique for describing the manifest content of communication

used for any type of content, any recorded medium, press, radio, video, etc.

Question 2

Advantages of quantitative content analysis

Answer 2

• emphasis on systematic sampling
• clear definitions of units and counting
• 100% reliability if the researcher uses computers because analysis will code all occurrences in the same way

Question 3

Disadvantages of quantitative content analysis

Answer 3

• address only questions do content
• really useful just for comparisons which limits its applicability
• validity in content analysis can be problematic in terms of relating its findings to the external world
• e.g. the frequency with which the word patriotism appears in a politicians speech increased over time does not entitle us to assume that in fact, the politician has become more patriotic over time.

Question 4

Data reduction

Answer 4

necessary to detect any patterns in the raw data and to make any such patterns comprehensible to readers of the final research report

Question 5

Content analysis

Answer 5

conventional use -> analyzing media content such as news, entertainment or advertising

the appeal of the web content analysis is ready and inexpensive access to a huge diversity of content from a variety of media types and sources worldwide

Question 6

Concerns with web sampling

Answer 6

• not fully knowing the relationship between the sample and the population from which it is drawn
• lack info about the source content of these data may be inaccessible
• samples may be bias for human reasons or technical reasons
• ability of software to recognize and analyze subtleties of human language and meaning for example, humor.

Question 7

Computer analysis of content

Answer 7

simplified by:
1) stemming - changing all variations of a word to its basic stem; e.g. fish, fishing, fished, fisherman

2) lemmatization - grouping words together based on their basic dictionary definition so that they can be analyzed as a single item; e.g. car and automobile do not have a common stem but both describe the word vehicle

3) stop words - high frequency words such as pronouns and prepositions

Question 8

Content analysis as quantitative and qualitative

Answer 8

scientific quantitative approach to the analysis of content, while allowing for qualitative subjective analyses

they coexist in any given study. one can use quantitative analysis to investigate qualitative phenomena such as emotional states
qualitative studies ultimately require qualitative interpretations.

Question 9

non directional research hypothesis

Answer 9

reflects a difference between groups but the direction of the difference is not specified

Question 10

directional research hypothesis

Answer 10

reflects a difference between groups and the direction of the difference is specified

Question 11

null

Answer 11

no relationship
population
indirectly tested
written with =

Question 12

research h

Answer 12

relationship
sample
directly tested
written with ><

Question 13

normal curve

Answer 13

1) symmetrical
2) asymptotic tail
3) mean median and mode are equal

if median and mean are different the distribution will be skewed to the left or to the right
the asymptotic tails mean they come closer and closer to the horizontal axis but never touch

Question 14

distance between mean and 1 stdev

Answer 14

34% of all cases under the curve

Question 15

1 and 2 stdevs

Answer 15

14% of cases under the curve

Question 16

2 and 3 stdevs

Answer 16

2% of cases under the curve

Question 17

3 stdevs<x

Answer 17

0.1% of cases under the curve

Question 18

z-score

Answer 18

standard score, comparable because they are standardized in units of stdevs

+ z scores = right of the mean, upper half
- z scores = left of the mean, lower half

84% fall below a z score of 1 (50% below the mean and 34% between mean and z score of 1)
16% of all scores fall above a z score of +1

Question 19

skewness

Answer 19

measure lack of symmetry
positively skewed - tail on the right
negatively skewed - tail on the left

Question 20

kurtosis

Answer 20

has to do with how flat or peaked a distribution appears
1) platykurtic - relatively flat distribution compared to a normal curve
2) leptokurtic - relatively peaked and taller distribution compared with a normal distribution

Question 21

significance level

Answer 21

risk associated with not being 100% confident that you observe in an experiment is due to the treatment or what was being tested

risk willing to take to reject a null hypothesis when it is actually true

Question 22

one sample Z TEST

Answer 22

comparison between a samples mean score and a populations mean score
utilized to compare a sample statistic with a population parameter to see if the sample is representative of the population

Question 23

when to perform a t-test for the significance of correlation coefficient?

Answer 23

1) im examining relationships between variables
2) im dealing with 2 VARIABLES

Question 24

when to perform regression, factor analysis or canonical analysis?

Answer 24

1) im examining relationships between variables
2) im dealing with MORE than 2 VARIABLES

Question 25

when to perform dependent samples t-test?

Answer 25

1) im examining differences between groups on one or more variables
2) participants are being tested more than once
3) im dealing with 2 GROUPS

Question 26

when to perform repeated measures ANOVA?

Answer 26

1) im examining differences between groups on one or more variables
2) participants are being tested more than once
3) im dealing with MORE than 2 GROUPS

Question 27

when to perform independent samples t-test?

Answer 27

1) im examining differences between groups on one or more variables
2) participants are being tested ONCE
3) im dealing with 2 GROUPS

Question 28

when to perform one way ANOVA?

Answer 28

1) im examining differences between groups on one or more variables
2) participate are being tested ONCE
3) im dealing with MORE than 2 GROUPS

Question 29

effect size

Answer 29

strength of a relationship between variables (correlation coefficient or value that estimate differences)

relationship between variables can also be apparent in the size of a difference between groups

small effect size - 0-0.2
medium effect size - 0.2-0.8
large effect size - 0.8 or higher

Question 30

inferential stats estimates

Answer 30

statistical inference: information that allows us to draw conclusions about the entire population from which we got our sample from

Question 31

point estimate

Answer 31

single number, best guess for estimation parameter
- x bar (mean) is a good point estimate for parameter mu (mean)
- one individual point estimate is no a good reference to see If the estimate is close to the population parameter we want to see

Question 32

interval estimate

Answer 32

range of values within which we expect the parameter to fall
probability that interval contains population value is called the confidence level

Question 33

hypotheses testing

Answer 33

expectations about the parameters researchers are interested in - hypotheses key ingredients of significance testing
we assess whether a hypothesis makes sense or not through significance test

on a significance test you always assume NH is true unless proven otherwise
rejected if AH has enough proof to make H0 wrong (doesn’t mean H0 is true)