Quiz 5 + 6
Testing Effect
A famous example of which threat to internal validity is known as the "Hawthorne Effect"
False
A frequency distribution table is the only way to present ratio-level data
False, two tailed
A hypothesis that specifies that there is a difference but does not specify the direction of the difference calls for a one-tailed hypothesis
True
A test of sampling adequacy is used to assess the representativeness of the sample.
True
ANOVA is an extension of the t-test
False
Although the mode can be identified for data captured at all four levels of measurement, it is the only measure of central tendency you can use with interval-level data.
It allows us to make predictions about one variable based upon the values of another variable
As an inferential statistic, regression is more powerful than mere correlation because?
Sweet Spot
Consumer insight/Brand insight
Correlation, Sequence/Order, Absence of other causal factors
Forms of evidence needed to establish causality
False
Frequency distributions can be used to describe data at only the nominal level of measurement
True
If "the tail" of a distribution goes to the right, it indicates a positive skew in the data
True
If you were statistically comparing a sample to the population from which it was drawn to prove how representative it is, you would be hoping to accept the null hypothesis.
True
It is generally assumed that 100% of the scores in a distribution of numbers will fall within plus or minus three standard deviations from the mean, especially if the distribution is believed to be normal
Coordination
Not one of the forms of evidence needed to establish causality
Post-Hoc Test
Ran after the ANOVA test
Ordinal
Rank the following, like a race w/o a clock, difference of the times between the finishers does not matter
True
Standard deviation provides a basis for estimating the probability of how frequently certain scores will occur based on sampling
Nominal-Level Variables
What is chi-square typically used for?
They must be translated into formal mathematical statements to be tested, always consist of a null and at least one alternative, may or may not specify the direction of the difference to be tested
What is true regarding hypotheses?
True
When it comes to research methods, experiments provide the ultimate level of certainty when it comes to establishing a causal relationship between two or more variables
True
When testing Mr. Pearson's r for statistical significance, the null hypothesis is almost always that the correlation between two variables in the population is zero.
About 68%
Suppose that television viewing is normally distributed with a mean of 2 hours per day and a standard deviation of .5 hours. Between 1.5 and 2.5 hours. (On the graph (1 hour: .136, 1.5: .34, 2: .34, 2.5: .136)
Interval
Temperature difference between 100 and 90 is the same as the difference between 90 and 80
True
The Central Limit Theorem predicts that statistical observations an infinite number of samples (such as a mean) drawn from the same population will take the form of a perfect normal distribution around the true population value.
True
The analysis of two variables simultaneously is called bivariate analysis
True
The area under a normal curve can be interpreted as a probability
False
The chi-square statistic and test for significance is typically used with data measured at the interval level.
True
The easiest way to collapse data in SPSS is by using the "recode" command
False
The internal validity threat called "mortality" doesn't actually mean that some of your research subjects could have died between the beginning of an experiment and the end
False
The mean, median, and mode are all measures of dispersion
Mesokurtic
The middle
Dependent
The purpose of most marketing research experimentation is to measure and compare the effect of the experimental treatments on one or more _____________ variables
Platykurtic
This type of kurtosis indicates scores that demonstrate greater-than-usual standard deviations, that is, the scores are more spread out
Chi-Square
To test whether the statistical results presented in a contingency table (cross tabulation) were statistically significant, you would normally use a ....
u1=u2
You are conducting a test of two new advertising campaign slogans to discover which is likely to be more effective by comparing mean scores on a measure of liking. u1 views one slogan and u2 sees the other one. Which of the following would be a correct and proper statement of the null to determine whether the difference in mean scores is statistically significant?
True
You could use regression analysis to determine if two variables are correlated.
Leptokurtic
the lowest
Nominal
the numerical values just "name" the attribute uniquely. No ordering of the cases is implied. For example, jersey numbers in basketball are measures at the nominal level. A player with number 30 is not more of anything than a player with number 15, and is certainly not twice whatever number 15 is
Ratio
there is always an absolute zero that is meaningful. This means that you can construct a meaningful fraction (or ratio) with a ratio variable. Weight is a ratio variable. In applied social research most "count" variables are ratio, for example, the number of clients in past six months. Why? Because you can have zero clients and because it is meaningful to say that "...we had twice as many clients in the past six months as we did in the previous six months."