Practice Test 3 Ch: 8, 9, 10, 15, 16, 17, 18, and 19 Flashcards
Warren is planning to conduct market research through in-depth interviews. His interview protocol includes a question comparing his company’s product to that of their main competitor (Solubin). Specifically, Warren plans to ask participants from the target market: “Wouldn’t you agree that Solubin is an inferior product?” What advice should you give to Warren?
Question 2Select one:
a.
Replace that question with one outlining the desirable features of his company’s product
b.
Use observation to reduce costs and increase the chance of uncovering “the hidden obvious”
c.
Avoid biased or leading questions
d.
Use a sequence record
Answer: c. Avoid biased or leading questions
Explanation: Warren’s proposed question, “Wouldn’t you agree that Solubin is an inferior product?” is a leading question, as it suggests an expected answer and could influence the participant’s response. In market research, it’s crucial to avoid bias and leading questions to ensure that the data collected is accurate and reflects the true perceptions and opinions of the participants. By asking unbiased and neutral questions, Warren can gather more reliable and valuable insights about his company’s product and its standing in comparison to competitors like Solubin.
Carol is interviewing employees of a firm regarding team cohesiveness by using an interview sequence with predetermined, open-ended questions. For each interview, Carol is required to use the same interview sequence to conduct the interview and cannot deviate from this sequence. Which type of interview is Carol conducting?
Question 1Select one:
a.
ethnographic interview
b.
formatted interview
c.
structured interview
d.
rigid interview
e.
moderated interview
Answer: c. structured interview
Explanation: A structured interview involves using a predetermined set of questions, asked in a specific sequence, without deviation. This approach ensures consistency across all interviews, allowing for more reliable comparisons of responses. Carol’s method of using a fixed interview sequence with open-ended questions for each employee interview aligns with the characteristics of a structured interview.
As the PEI bioscience industry started to take shape, Dr. Udo Krautwurst, a UPEI anthropologist, conducted field research and later published a book – Culturing Bioscience – about the people working in that industry. Dr. Krautwurst spent time in labs and got involved in some of the work being conducted to understand the culture. “I got to do a little bit of stuff – stuff I couldn’t break” since multi-million dollar equipment was involved. “It gave me a sense of process and the steps people have to go through.” Which of the following best characterizes Dr. Krautwurst’s research method?
Question 3Select one:
a.
participant observation
b.
intensive lab research
c.
content analysis
d.
structured observation research
e.
concealed observation protocol
Answer: a. participant observation
Explanation: Participant observation is a qualitative research method in anthropology where the researcher immerses themselves in the environment and activities of the people being studied. This method often involves participating in the daily activities of the subjects to gain a deeper understanding of their culture and practices. Dr. Krautwurst’s involvement in the labs and participation in some of the work, albeit in a limited capacity due to the nature of the equipment, is indicative of participant observation. This approach allowed him to gain firsthand experience and insight into the culture and processes of the bioscience industry in PEI.
Researchers posed as retail clerks to watch shoppers unobtrusively in natural, public settings. The researchers performed clerical tasks and wore the company’s uniform. Which of the following best describes the method used?
Question 4Select one:
a.
Bystander, concealed
b.
Controlled, unconcealed
c.
Uncontrolled, unconcealed
d.
Uncontrolled, concealed
Answer: d. Uncontrolled, concealed
Explanation: In this method, researchers are conducting observation in a natural setting without manipulating any variables (hence ‘uncontrolled’). They are also doing this in a concealed manner, meaning that the subjects (shoppers) are unaware that they are being observed for research purposes. The researchers’ disguise as retail clerks and their engagement in clerical tasks further ensure that their presence and observation activities remain unnoticed by the shoppers. This approach allows for the collection of natural, unbiased behavioral data in a public setting.
Which is the most important consideration when developing closed response options for a questionnaire?
Question 5Select one:
a.
mutually exclusive and collectively exhaustive
b.
ratio-level data
c.
recode reverse-keyed items
d.
Delphi scaling and sequencing
Answer: a. mutually exclusive and collectively exhaustive
Explanation: When designing closed response options (such as multiple choice questions), it is crucial to ensure that the options are mutually exclusive and collectively exhaustive. Mutually exclusive options mean that each response is distinct and does not overlap with other options, ensuring that respondents can choose one option that best fits their answer. Collectively exhaustive means that all possible answers are included in the options, leaving no respondent’s potential answer unaccounted for. This approach ensures that the data collected is both accurate and comprehensive.
Drs. Ashton and Lee are prominent personality researchers who will soon be collecting personality data in South Korea. Dr. Lee has translated their well-established English questionnaire into Korean. What should the next step be in this project?
Question 6Select one:
a.
Personally-administer the questionnaires
b.
Question sequencing
c.
Frequency distribution
d.
Back translation
Answer: d. Back translation
Explanation: Back translation is a process used in research to ensure the accuracy of translated materials. After Dr. Lee has translated the English questionnaire into Korean, it should be translated back into English by an independent translator who has not seen the original English version. This process helps to identify any discrepancies or misunderstandings in the translation, ensuring that the meaning of the questions remains consistent across languages. This step is crucial, especially in personality research, where the precision of language is vital for valid and reliable results.
Louis is assigning a number to a particular response so the answer can be entered into a database. He assigns a 5 for “strongly agree” and a 1 for “strongly disagree,” and the points in between get assigned 2, 3, or 4. What is Louis doing?
Question 7Select one:
a.
analyzing the data
b.
coding
c.
developing the frequency distribution
d.
measuring the kurtosis
e.
calculating the mean
Answer: b. coding
Explanation: Coding in the context of survey research involves assigning numerical values to different response options so that the data can be easily entered, processed, and analyzed in a database. By assigning numbers like 5 for “strongly agree” and 1 for “strongly disagree,” Louis is converting qualitative responses into a quantitative format, which is a fundamental part of data coding. This process is essential for statistical analysis and helps in transforming raw survey data into a format that can be systematically analyzed.
What type of data are necessary to calculate the mean?
Question 8Select one:
a.
interval or ordinal
b.
ratio or nominal
c.
nominal or ordinal
d.
interval or ratio
Answer: d. interval or ratio
Explanation: The mean, which is a measure of central tendency, requires data that can be meaningfully averaged. Interval data and ratio data are both suitable for this purpose. Interval data has meaningful distances between measurements but lacks a true zero point (such as temperature in Celsius or Fahrenheit). Ratio data, on the other hand, has both meaningful distances between measurements and a true zero point (like weight or height). Both these types of data allow for the calculation of an average, as they are quantitative and continuous in nature. Nominal and ordinal data, being categorical and not based on numerical differences, are not suitable for calculating a mean.
Cynthia has nominal data and wants to calculate a measure of central tendency. Which measure is most appropriate?
Question 9Select one:
a.
mean
b.
median
c.
mode
d.
standard deviation
e.
kurtosis
Answer: c. mode
Explanation: The mode is the most suitable measure of central tendency for nominal data. Nominal data are categorical and do not have an inherent order or numerical value. The mode, being the value that occurs most frequently in a data set, can be applied to any type of data, including nominal. It identifies the most common category or value in the dataset. Measures like mean and median require numerical data with an inherent order, which is not the case with nominal data. Standard deviation and kurtosis are also not applicable as they require interval or ratio data.
A simple measure of dispersion defines the spread of the data and is the distance between the largest and the smallest values of a sample frequency distribution. What is the name of that measure?
Question 10Select one:
a.
variance
b.
skewness
c.
kurtosis
d.
range
e.
difference
Answer: d. range
Explanation: The range is a basic statistical measure used to describe the dispersion or spread in a set of data. It is calculated by subtracting the smallest value in the dataset from the largest value. The range gives a quick sense of the width of the distribution of the data, indicating how spread out the values are. It is a simple and straightforward measure but does not provide information about the distribution of values within the range.
A hypothesis stated as “No relationship exists between employee tenure and satisfaction” is best described as what kind of hypothesis?
Question 11Select one:
a.
common
b.
base
c.
null
d.
alternative
e.
sample
Answer: c. null hypothesis
Explanation: The null hypothesis is a type of hypothesis used in statistics that proposes there is no significant effect or relationship between two variables. It is often denoted as H0 and is typically the hypothesis that researchers aim to test against. In this case, the statement “No relationship exists between employee tenure and satisfaction” is a classic example of a null hypothesis, as it posits the absence of a relationship or effect. The alternative hypothesis (H1 or Ha ), on the other hand, would propose that there is a significant relationship or effect.
Data are measured using a metric (i.e., interval or ratio) scale and the sample size is large. Assume the sample data are collected from populations with normal (bell-shaped) distributions. What general type of statistics is most appropriate?
Question 12Select one:
a.
parametric
b.
nonparametric
c.
chi-square
d.
ANOVA
e.
MANOVA
Answer: a. parametric
Explanation: Parametric statistical methods are most suitable when the data meet certain assumptions, including being measured on an interval or ratio scale and coming from a normally distributed population. These methods rely on assumptions about the population parameters and are typically more powerful and precise when these assumptions are met. Examples of parametric tests include t-tests, ANOVA, and linear regression. Nonparametric methods, on the other hand, are used when data do not meet these assumptions or are measured on an ordinal or nominal scale. While specific tests like chi-square, ANOVA, and MANOVA (options c, d, and e) fall under the umbrella of parametric statistics, the most general and appropriate category given the conditions described is parametric statistics.
When is a “one-way ANOVA” used?
Question 13Select one:
a.
A directional hypothesis is being tested
b.
No follow-up tests will be performed
c.
There is one independent variable with three or more levels
d.
There are no more than two treatment levels for the independent variable
Answer: c. There is one independent variable with three or more levels
Explanation: One-way ANOVA (Analysis of Variance) is a statistical technique used to compare the means of three or more groups to see if at least one group mean is significantly different from the others. These groups are different levels of a single independent variable. For instance, if you were testing the effect of different diets (vegetarian, vegan, omnivore, etc.) on weight loss, where the type of diet is the independent variable and weight loss is the dependent variable, a one-way ANOVA would be suitable. This method is not limited to directional hypotheses (option a) and can be followed by post hoc tests if needed (contrary to option b). It is specifically used when there are more than two levels or groups in the independent variable, distinguishing it from a t-test which is typically used for comparing two groups (counter to option d).
Which type of error occurs when the sample results lead to the rejection of the null hypothesis when it is, in fact, true?
Question 14Select one:
a.
Type 0
b.
Type I
c.
Type II
d.
Type III
e.
Type IV
Answer: b. Type I
Explanation: A Type I error, also known as a “false positive,” occurs in hypothesis testing when the null hypothesis is incorrectly rejected. This means that the researcher concludes that there is a significant effect or relationship when, in reality, there isn’t one. The probability of making a Type I error is denoted by the alpha level (α), which is typically set at 0.05 (or 5%). This is different from a Type II error (a “false negative”), where the researcher fails to reject the null hypothesis when it is false. There are no recognized errors labeled as Type 0, Type III, or Type IV in standard statistical terminology.
What does the size of the correlation coefficient indicate?
Question 15Select one:
a.
presence of a relationship
b.
strength of the association
c.
curvilinearity of the relationship
d.
multicollinearity of the relationship
Answer: b. strength of the association
Explanation: The correlation coefficient, often represented as r, measures the strength and direction of a linear relationship between two variables. Its value ranges from -1 to +1. A correlation coefficient close to +1 indicates a strong positive linear relationship, close to -1 indicates a strong negative linear relationship, and around 0 suggests no linear relationship. The size (absolute value) of the correlation coefficient reflects the strength of the association, with larger absolute values indicating stronger relationships. It does not, however, indicate the presence of a relationship (as a value of 0 could mean no linear relationship), the curvilinearity of the relationship, or multicollinearity (which involves more than two variables).
Comment on the descriptive statistics (i.e., means, standard deviations) and internal consistency reliabilities in the table below adapted from Siu et al. (2013) and summarize the correlation results, taking into account the strength, direction, and statistical significance of the bivariate relationships.
Based on the provided table adapted from Siu et al. (2013), the descriptive statistics indicate that the average age of the sample is 31.9 years with a standard deviation (SD) of 7.4, suggesting a moderate spread around the mean age. The average tenure is 4.3 years with a larger spread (SD = 5.2). Social support has an average score of 3.58 (SD = 0.63), interpersonal conflict has an average score of 1.96 (SD = 1.07), organizational politics is rated at an average of 2.17 (SD = 1.17), and job performance is rated at an average of 4.77 (SD = 0.61), on a scale of 1 to 6.
The internal consistency reliabilities (Cronbach’s Alpha) for the scales are acceptable, ranging from .77 to .88, except for age and tenure which are single-item variables and therefore do not have an alpha value. An alpha of .70 or higher is generally considered acceptable for social science research, suggesting that the measures for social support, interpersonal conflict, organizational politics, and job performance are reliable.
The correlation results show several significant relationships:
- Tenure and Age (r = .57, p < .001): There’s a strong, positive correlation between tenure and age, indicating that as age increases, tenure tends to increase as well.
- Organizational Politics and Job Performance (r = -.15, p < .05): A weak, negative correlation suggests that higher perceptions of organizational politics are associated with lower job performance.
- Interpersonal Conflict and Job Performance (r = .13, p < .05): This weak, positive correlation is somewhat counterintuitive, indicating that higher reports of interpersonal conflict are associated with better job performance, although this is likely not a causal relationship.
- Social Support and Tenure (r = -.03, p > .05): The correlation is very weak and not statistically significant, indicating no meaningful relationship between social support and tenure.
- Interpersonal Conflict and Organizational Politics (r = .01 to .02, p > .05): These correlations are also very weak and not statistically significant, suggesting no meaningful relationship between interpersonal conflict and organizational politics.
The significant correlations should be interpreted with caution, as correlation does not imply causation. Additionally, weak correlations, even if statistically significant, do not indicate a strong relationship between variables.
