Đề 1 – Bài tập, đề thi trắc nghiệm online Nguyên lý thống kê

A A. Paired t-test B B. ANOVA C C. Independent samples t-test D D. Chi-square test

A A. Temperature in Celsius B B. Colors of cars in a parking lot C C. Customer satisfaction ratings (e.g., Very Dissatisfied, Dissatisfied, Neutral, Satisfied, Very Satisfied) D D. Heights of students in a class

A A. The hypothesis that the researcher is trying to prove. B B. The hypothesis that there is no effect or no difference. C C. The hypothesis that is always true. D D. The hypothesis based on the sample data.

A A. The slope of the regression line. B B. The correlation coefficient between the variables. C C. The proportion of variance in the dependent variable that is predictable from the independent variable(s). D D. The p-value of the regression model.

A A. Type I error is failing to reject a false null hypothesis, while Type II error is rejecting a true null hypothesis. B B. Type I error is rejecting a true null hypothesis, while Type II error is failing to reject a false null hypothesis. C C. Type I error occurs with small sample sizes, while Type II error occurs with large sample sizes. D D. Type I error is related to the p-value, while Type II error is related to the confidence interval.

A A. To prove the null hypothesis is true. B B. To calculate the sample mean and standard deviation. C C. To determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. D D. To describe the characteristics of a sample.

A A. The result is important in a practical sense. B B. The result is very likely to be due to chance alone. C C. The observed effect is unlikely to have occurred by random chance alone, assuming the null hypothesis is true. D D. The sample size is very large.

A A. It guarantees that the sample mean will be exactly equal to the population mean. B B. It eliminates the need for statistical inference. C C. It helps to minimize bias and ensures that the sample is more likely to be representative of the population. D D. It makes the data collection process faster and cheaper.

A A. The process of summarizing data using graphs and tables. B B. The method of collecting data from every member of a population. C C. The practice of using sample data to make generalizations or conclusions about a larger population. D D. The calculation of basic statistics like mean, median, and mode.

A A. A theorem stating that the sample mean is always equal to the population mean. B B. A theorem that applies only to normally distributed populations. C C. A theorem stating that the distribution of sample means approaches a normal distribution as the sample size increases, regardless of the population's distribution. D D. A theorem used to calculate confidence intervals for small sample sizes.

A A. Mean B B. Median C C. Mode D D. Standard Deviation

A A. Random error in measurements. B B. Systematic error that consistently distorts results in one direction. C C. The variability of a statistic across different samples. D D. The standard deviation of the sample.

A A. A subset of individuals selected from a larger group. B B. The entire group of individuals, objects, or events of interest in a study. C C. The average of all values in a dataset. D D. The range of values in a dataset.

A A. To make predictions about future events. B B. To draw conclusions about a population based on a sample. C C. To summarize and describe the main features of a dataset. D D. To establish cause-and-effect relationships between variables.

A A. It is very likely to make a Type I error. B B. It is very likely to fail to reject a false null hypothesis. C C. It is very likely to correctly reject a false null hypothesis. D D. It is very likely to reject a true null hypothesis.

A A. To provide a single, exact estimate of a population parameter. B B. To provide a range of values that is likely to contain the true population parameter with a certain level of confidence. C C. To determine if the null hypothesis should be rejected. D D. To eliminate sampling error.

A A. Mean B B. Median C C. Standard Deviation D D. Mode

A A. To select participants based on convenience. B B. To divide the population into subgroups (strata) and then randomly sample from each stratum. C C. To sample every nth individual in a population. D D. To select clusters of individuals that are geographically close.

A A. The distribution of values in a single sample. B B. The distribution of a statistic (e.g., sample mean) calculated from all possible samples of a given size from a population. C C. The distribution of the population. D D. Any distribution used for sampling.

A A. Assumptions are not important if the sample size is large enough. B B. Violating assumptions can lead to unreliable or invalid results from the test. C C. Assumptions only affect the p-value, not the conclusion of the test. D D. All statistical tests have the same assumptions.

A A. Scatter plot B B. Bar chart C C. Histogram D D. Pie chart

A A. Ordinal data B B. Interval data C C. Nominal data D D. Ratio data

A A. When the data is normally distributed. B B. When the data is categorical. C C. When the data is skewed or contains outliers. D D. When you want to calculate the average of all values.

A A. Central tendency. B B. The median value. C C. Dispersion or spread of data points around the mean. D D. The most frequent value.

A A. It is when the dependent variable is categorical; it's not a concern. B B. It is high correlation between independent variables; it can lead to unstable coefficient estimates and difficulty in determining the individual effect of each predictor. C C. It is low correlation between independent variables; it improves the model. D D. It refers to non-linearity in the relationship between variables; it's always desirable.

A A. The probability that the null hypothesis is true. B B. The probability of making a Type I error. C C. The probability of observing data as extreme as, or more extreme than, the observed data if the null hypothesis were true. D D. The probability that the alternative hypothesis is true.

A A. Interval scales have a true zero point, while ratio scales do not. B B. Ratio scales have a true zero point, while interval scales do not. C C. Interval scales are categorical, while ratio scales are numerical. D D. There is no difference; the terms are interchangeable.

A A. The cause-and-effect relationship between two variables. B B. A measure of the linear association between two variables. C C. The difference between two means. D D. The variability of a single variable.

A A. As sample size increases, the margin of error increases. B B. As sample size increases, the margin of error decreases. C C. Sample size and margin of error are unrelated. D D. The margin of error is determined only by the confidence level, not sample size.

A A. Showing the relationship between two categorical variables. B B. Comparing the means of multiple groups. C C. Displaying the distribution of a numerical variable, including median, quartiles, and outliers. D D. Showing the frequency of categorical data.