What is the main advantage of repeated measures design?

Controls individual differences

What does the law of large numbers state?

Closer sample mean to population

What is the significance of the z-score formula?

Compares sample mean to population mean

What is the role of degrees of freedom?

Influences t distribution shape

How is the standard error calculated?

Sample size and standard deviation

What is the significance of p-value?

Indicates significance of results

What does r² represent in statistics?

Proportion of variance explained

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PSYC 3010 Chapter 7B + PSYC 3010 Chapter 7A + PSYC 3010 Chapter 10A + PSYC 3010 Chapter 10B + P

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Questions 121

Answers

1
What is the relationship between sample size and error?
Larger size, larger error
Smaller size, smaller error
Larger size, smaller error
No relationship
2
What happens to standard error as sample size increases?
Decreases
Remains constant
Increases
Varies randomly
3
What does a larger sample size imply?
Less sampling error
Higher bias
Increased variability
More sampling error
4
What is the expected outcome of repeated sampling?
Fluctuating sample means
Identical sample means
Consistent sample means
No variability
5
What is the role of random sampling?
Ensure identical results
Limit sample size
Increase sampling error
Minimize bias in samples
6
What does a non-directional test imply?
Two-tailed hypothesis test
One-tailed hypothesis test
Effect size measure
Sample size estimation
7
Which assumption is crucial for t tests?
Independence of observations
Equal sample sizes
Large sample size
Non-normal distribution
8
What is the main advantage of repeated measures design?
Simpler data analysis
Minimizes carryover effects
Controls individual differences
Requires more participants
9
Why is t-statistic important?
For small samples
For population data
For qualitative data
For large samples
10
What is the primary goal of using larger samples?
Reduce sampling error
Increase variability
Ensure identical results
Limit population size
11
How does t-distribution differ from normal distribution?
Flatter and spread out
More peaked
Identical shape
Less variability
12
How does sample size affect error?
Smaller sample, smaller error
Sample size has no effect
Larger sample, larger error
Larger sample, smaller error
13
Which design minimizes carryover effects?
Within-subjects design
Independent measures design
Repeated measures design
Between-subjects design
14
What does a p-value indicate?
Effect size magnitude
Sample size effect
Probability of null hypothesis
Confidence interval width
15
What happens with larger sample sizes?
Larger error
Lower t values
Smaller error
Higher variance
16
What does a confidence interval containing zero imply?
No significant effect
Significant effect
Low sample size
High variance
17
How does standard error relate to confidence intervals?
Calculates population mean
Estimates true mean range
Determines sample size
Defines sampling error
18
What is the primary purpose of the t-test?
Determine population parameters
Compare means of groups
Calculate variances
Assess sample sizes
19
What does a t statistic indicate?
Population variance
Difference between groups
Sample size only
Effect size only
20
What is the primary focus of hypothesis testing?
Determining population size
Assessing group differences
Evaluating data variability
Calculating sample means
21
What happens as sample size increases?
Closer to population mean
Increased sampling error
More variability
Less accuracy
22
What does the standard deviation of sample means represent?
Population mean accuracy
Variability of sample means
Sample size effect
Confidence interval width
23
What does a lower standard error suggest?
Lower sample size
Higher sample size
More variability
Less variability
24
What does the t statistic compare?
Two population means
Two sample variances
Sample mean to population mean
Sample variance to population variance
25
What does a significant t statistic suggest?
Homogeneity of variance
Equal variances
No difference between groups
Difference between groups
26
What is the role of standard deviation in t-tests?
Defines population mean
Calculates t-value
Indicates sample size
Measures data spread
27
What does the t statistic measure?
Variance of samples
Difference between means
Sample size effect
Population parameter accuracy
28
What is the shape of the distribution of sample means?
Bimodal
Uniformly distributed
Skewed left
Approximately normal
29
What does the law of large numbers state?
All samples are identical
Sample size does not matter
Random sampling is unnecessary
Closer sample mean to population
30
What does the critical region indicate?
Increase sample size
Accept null hypothesis
Reject null hypothesis
Decrease variance
31
What does a 95% confidence interval represent?
Standard deviation range
Population size range
True mean range
Sample mean range
32
What is the expected value of sample means?
Always higher than population mean
Equal to population mean
Always lower than population mean
Varies with sample size
33
What does the estimated standard error indicate?
Exact mean difference
Sample size impact
Average distance between means
Variance of samples
34
What is the significance of the z-score formula?
Calculates sample mean only
Compares sample mean to population mean
Determines sample size
Estimates population size
35
What is the role of degrees of freedom?
Influences t distribution shape
Estimates population mean
Calculates effect size
Determines sample size
36
What indicates a significant treatment effect?
Interval is narrow
Interval does not contain zero
Interval contains zero
Interval is wide
37
What does the 95% confidence interval represent?
Sample mean only
Exact population mean
Range of population means
Standard deviation range
38
What is the purpose of hypothesis testing?
Determine treatment effects
Measure effect size only
Estimate population variance
Calculate sample size
39
How is degrees of freedom calculated?
Sum of individual df
Sum of sample variances
Average of sample means
Sum of sample sizes
40
What does the term 'sampling distribution' refer to?
Statistics from samples
Single sample results
Random selection only
Scores from population
41
What is the first step in hypothesis testing?
Choose significance level
Calculate t-value
Collect data
State the hypotheses
42
What is the critical value used for?
To find sample mean
To determine significance
To calculate variance
To estimate population size
43
How is sampling error defined?
Exact measurement
Difference from population
Random chance only
Statistical mistake
44
What increases confidence interval width?
Higher confidence level
Lower alpha level
Larger sample size
Smaller standard error
45
What is a paired t-test?
Calculates effect size
Compares independent samples
Compares same group over time
Estimates population variance
46
Which factor minimizes sampling error?
Single observation
Smaller sample size
Random selection
Larger sample size
47
How is the standard error calculated?
Confidence intervals
Population mean only
Sample size and standard deviation
Random sampling only
48
What is the significance of p-value?
Indicates sample size
Indicates mean difference
Indicates variance
Indicates significance of results
49
What does r² represent in statistics?
Population mean
Sample variance
Standard error
Proportion of variance explained
50
What does a z-score indicate?
Population size effect
Sample size effect
Distance from mean
Standard deviation only
51
What does Cohen's d measure?
Sample size
Effect size
Standard deviation
Variance only
52
What is effect size?
Sample size measure
Strength of relationship
Statistical significance only
Type of hypothesis test
53
What does the t-distribution approximate?
Normal distribution
Binomial distribution
Uniform distribution
Exponential distribution
54
What influences the t-distribution shape?
Sample size
Sample mean
Degrees of freedom
Population variance
55
What is a potential risk in within-subjects design?
Independent observations
Fewer participants needed
Order effects
Simpler execution
56
What does r² represent?
Sample mean difference
Total variability explained
Population mean estimate
Standard deviation measure
57
What is the relationship between sample size and sampling error?
Increases error randomly
No relationship
Larger size reduces error
Smaller size reduces error
58
What is the purpose of reporting descriptive statistics?
To reduce clarity
To confuse readers
To summarize data
To increase complexity
59
What is the first step in hypothesis testing?
Select alpha level
Calculate t statistic
State the hypothesis
Collect data
60
What does a significant Levene's test indicate?
Homogeneity of variances
Unequal variances across groups
Equal variances across groups
No significant difference
61
What does a flatter t-distribution indicate?
More variability
Identical to normal
Less variability
Higher sample size
62
What is the effect of increasing sample size on standard error?
Decreases standard error
No effect
Varies randomly
Increases standard error
63
What is the expected value of M?
Mean of sample means
Sampling error measure
Standard deviation
Population mean value
64
What does a large t value indicate?
Low effect size
Small sample size
Significant difference
High variance
65
What is the effect of increased variance?
Higher sample size
Lower sample variance
Higher t values
Lower t values
66
What does the t-statistic help to test?
Sample variance
Unknown population mean
Sample size
Known population mean
67
What is a key assumption of t-tests?
Unequal variances
Independent samples
Dependent samples
Non-normal data
68
What does the term 'independent measures' imply?
Same group for conditions
Correlated observations
Different groups for conditions
Repeated measures design
69
What is a confidence interval?
Sample size measure
Range of population values
Effect size measure
Single point estimate
70
Why square deviations in variance calculation?
To remove negative values
To reduce data complexity
To simplify calculations
To emphasize smaller deviations
71
What is the final step in hypothesis testing?
State the hypothesis
Collect data
Make a decision
Calculate variance
72
What is a disadvantage of between-subjects design?
Requires more participants
Minimizes individual differences
Requires fewer participants
Simpler data analysis
73
What does the term 'carryover effects' refer to?
Variance of samples
Influence of previous conditions
Sample size impact
Independent observations
74
What does homogeneity of variance imply?
Different variances
No variances
Similar variances
Only one variance
75
What is a characteristic of sample means?
Randomly distributed
Always identical
Only one mode
Piles around population mean
76
What is the relationship between sample size and standard error?
No relationship
Error is constant
Larger size reduces error
Smaller size increases error
77
What does Cohen's d indicate?
Sample size effect
Statistical significance
Variance comparison
Effect size magnitude
78
What is the purpose of a one-tailed test?
To reduce error
To predict direction
To compare two means
To increase sample size
79
What does a smaller standard error indicate?
More variability
More confidence
Larger sample size
Less confidence
80
What is the central limit theorem?
Sampling error definition
Population variance
Single score analysis
Shape of sample means
81
What does the standard deviation of sample means indicate?
Single score variability
Variability of sample means
Exact sample size
Population mean accuracy
82
Which value indicates lower variability?
Higher standard error
Sample mean
Population mean
Lower standard error
83
What does standard error of M measure?
Exact population mean
Distance between M and μ
Sample size only
Population variance
84
What is the role of confidence intervals?
Determine sample variance
Calculate sample size
Estimate population mean
Predict future outcomes
85
What does standard error quantify?
Sample size effects
Sample means variability
Population mean accuracy
Data collection methods
86
How does pooled variance improve analysis?
Focuses on individual variances
Simplifies data interpretation
Combines variances accurately
Ignores sample sizes
87
What does Hartley’s F-max test assess?
Sample size
Sample distribution
Sample means
Homogeneity of variance
88
What does the term 'sampling distribution' refer to?
Distribution of z-scores
Distribution of standard deviations
Distribution of population data
Distribution of sample means
89
What is the impact of individual differences in between-subjects design?
May affect outcomes
Simplifies analysis
Enhances data accuracy
Minimizes variability
90
What is a key feature of within-subjects design?
Correlated observations
Different participants per condition
Independent observations
Same participants across conditions
91
What happens if t-value exceeds critical value?
Reject null hypothesis
No conclusion
Accept null hypothesis
Increase sample size
92
What is the primary use of the distribution of sample means?
Determine sample accuracy
Estimate population size
Calculate standard deviation
Find probabilities of samples
93
What does pooled variance estimate measure?
Sample size only
Standard deviation only
Variability between samples
Population mean difference
94
What does a sampling error indicate?
Natural discrepancy
Exact population result
Mistake in sampling
Random chance only
95
What does sampling error represent?
Difference in preferences
Exact population result
Random sampling error
Measurement mistake
96
How does sample size affect standard error?
Increases standard error
No effect
Varies randomly
Decreases standard error
97
What does the variability of sampling error affect?
Confidence interval width
Standard deviation only
Population mean accuracy
Sample mean accuracy
98
What does 'degrees of freedom' represent?
Independent scores
Sample mean
Population variance
Total sample size
99
Which factor affects the t statistic?
Sample size
Sample age
Sample color
Sample location
100
What is the formula for standard error?
√s/n
s/n
s/√n
n/s
101
What does a larger standard error suggest?
More reliable estimate
Increased sample size
Less reliable estimate
No effect on results
102
What is the expected outcome of larger sample sizes?
More random results
Less accurate results
Closer to true population
Increased sampling error
103
What is the role of the alternative hypothesis?
Assesses sample size
Suggests a difference exists
Confirms null hypothesis
Indicates equal means
104
What does a z-score represent?
Location in distribution
Sample size only
Population mean
Standard deviation
105
What is the significance of a sampling distribution?
Population frequency only
Single sample analysis
Collection of sample means
Random sampling only
106
What is the critical region?
Sample mean range
Area for accepting H0
Area for rejecting H0
Effect size measure
107
What is the significance level commonly set at?
0.01
0.05
0.10
0.50
108
What is the significance of the t-test in research?
Determines group differences
Assesses data variability
Measures sample size
Calculates population parameters
109
What is the role of the Central Limit Theorem?
Calculates standard deviation
Describes sample mean distribution
Estimates confidence intervals
Defines population size
110
What does the t-statistic formula estimate?
Population variance
Population mean
Sample mean
Sample variance
111
What is sampling error?
Standard deviation of samples
Confidence interval error
Difference between sample and population mean
Error in data collection
112
What is the purpose of hypothesis testing?
To infer population conditions
To analyze variance
To prove a theory
To collect data
113
What does a significant p-value indicate?
No effect observed
Accept null hypothesis
Equal means confirmed
Reject null hypothesis
114
What is the null hypothesis (H0)?
Always false
No significant difference
There is a difference
Always true
115
What does a small Cohen's d indicate?
Minimal practical impact
Statistical significance only
Large effect size
High variance
116
What is the importance of sample variance?
Indicates sample size
Confirms null hypothesis
Measures data spread
Calculates population mean
117
What is a one-sample t-test used for?
Compare two groups
Estimate effect size
Compare sample to population
Assess variance only
118
What is a two-sample t-test?
Assesses paired observations
Compares two independent samples
Compares one sample to population
Calculates variance only
119
What is the null hypothesis in independent-measures test?
Variances are different
Variances are equal
Means are equal
Means are different
120
What does a higher standard error indicate?
Tighter clustering
Lower sample size
More variability
Higher population mean
121
What does a normal distribution imply?
Random outcomes only
No variability
Predictable probabilities
All scores identical

PSYC 3010 Chapter 7B + PSYC 3010 Chapter 7A + PSYC 3010 Chapter 10A + PSYC 3010 Chapter 10B + P Flashcards | StudBud