Stats Final T/F review

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A dependent variable is characterized by a small number of levels of treatment.

F

A histogram is used to present the frequencies of a qualitative variable.

F

A negatively skewed curve has a thin point directed to the right side of a graph.

F

A parameter is a characteristic of a sample.

F

Bimodal distributions are an example of a normal distribution.

F

Calculating a deviation score requires a standard deviation.

F

Extreme scores on the normal curve are those between the mean and the median.

F

The denominator of a t test is a difference between means.

F

The formula for effect size index, d, has the sample mean in the denominator.

F

The formula for the standard deviation of a sample used to estimate σ has N in the denominator.

F

The mean is an appropriate measure of central tendency for skewed distributions.

F

The mean is an appropriate measure of central tendency with open-ended distributions.

F

The numbers from a nominal scale convey greater concepts of greater than and less than.

F

The researcher chooses the values of the dependent variable in an experiment.

F

To find the overall mean using samples of different sizes, add the two means and divide by 2.

F

Values of d larger than 1.00 are not possible.

F

You can determine the mode of a distribution from a boxplot presented in the textbook.

F

You can determine the standard deviation of a distribution from boxplots presented in the textbook.

F

Your text supports the assertion that you can prove anything with statistics.

F

z scores are used to indicate the central tendency of a distribution.

F

An effect size index of .05 or greater is considered larger.

F (.8 or greater)

If an urn contains 2 red balls, 2 blue balls, and 1 green ball, the probability of drawing a red ball is .50.

F (2/5 = .40)

A univariate distribution is required to calculate a correlation coefficient.

F (bivariate distribution is required)

As N increases, the standard error of the mean increases.

F (decreases - Central Limit Theorem)

The numerator of the z score in Chapter 6 is a standard deviation.

F (deviation score)

Equal distances on the X axis are associated with equal proportions of the normal curve.

F (its a normal curve -bell shaped. Much more area between -1 and 1 than between 3 and 4.)

A bar graph is used to present the frequencies of a quantitative variable.

F (qualitative variable)

By using random samples, uncertainty about the conclusion can be eliminated.

F (reduced but not eliminated)

To know degrees of freedom, you must know the sample mean.

F (usually just N)

A Type 1 error is possible when the null hypothesis is true.

T

A characteristic of the mean is that Σ(x-x̄) =0.

T

A line graph shows the relationship between two variables.

T

A point on the normal curve with .35 of the curve beyond it has .15 between it and the mean.

T

A population with a bimodal distribution could produce a normally distributed sampling distribution.

T

A population with a rectangular distribution could produce a normally distributed sampling distribution.

T

A scatterplot is a graph of a bivariate distribution.

T

A z score of -1.05 is possible.

T

An extraneous variable can influence the values of the dependent variable in an experiment.

T

Bell-shaped and rectangular distributions are symmetrical.

T

Coorelation soefficients range from -1.00 to 1.00.

T

Correlation coefficients cannot be used to establish a cause and effect relationship.

T

Extreme scores on the normal curve are those far from the mean.

T

Finding the interquartile range first requires a calculation of percentiles.

T

For a bivariate distribution with 10 pairs of scores, N+10.

T

For continuous data that are positively skewed, the mean is usually larger than the median.

T

Horizontal axis, x-axis, and abscissa are all names for the same line.

T

If a bivariate distribution is not linear, r will not show the degree of relationship between two variables.

T

If a difference is statistically significant, the null hypothesis was rejected.

T

If the null hypothesis is retained, the difference is not statistically significant.

T

Meaningful confidence intervals of 90, 95, and 99 percent could be calculated for a single sample mean.

T

On a ratio scale, zero means that no amount was present.

T

Sampling distributions are based on random samples.

T

Sampling distributions are the basis of probability statements in statistics.

T

Statements such as "twice as much" and "half as much" are permissible if the variable is measured on a ratio scale.

T

The coefficient of determination is the square of r.

T

The greater the overlap of two distributions, the smaller the size of d.

T

The inflection points on the normal curve are at z=-1 and z=+1.

T

The location of the median is found using the formula, (N+1)/2.

T

The mode is an appropriate measure of central tendency for any of the four scales of measurement.

T

The probability figure that is the conventional cut-off for null hypothesis statistical testing is .05.

T

The reliability of a test can be measured using a correlation coefficient.

T

The total area of each theoretical distribution described in Chapter 6 was 1.00.

T

To determine how much difference there is between two distributions, calculate d.

T

To look up a t value in the t distribution table, you must know sample size.

T

To select a random sample, every member of the population must be identified.

T

To use a sample is to agree to accept some uncertainty about the results.

T

You can determine the 25th and 7th percentile from boxplots presented in the textbook.

T

You can determine the interquartile range of a distribution from a boxplot presented in the textbook.

T

You can determine the skew of a distribution from a boxplot presented in the textbook.

T

z scores are used to describe individual scores.

T

The Central Limit Theorem describes the form of a sampling distribution.

T (CLT - as N increases, sample mean gets closer to μ)

The normal distribution is symmetrical about the median.

T (in a normal distribution, median = mean)

The sample mean is always in the exact middle of a confidence interval.

T (sample mean, not pop. mean)

The regression coefficient, a, tells where the regression line crosses the Y axis.

T (y=a+bx)


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