The statement is true. The correlation coefficient is a statistical measure that shows the strength and direction of the relationship between two variables. The coefficient ranges from -1 to +1, where a positive value indicates a positive correlation and a negative value indicates a negative correlation. A coefficient near 1 indicates a strong positive correlation, which means that the larger values of one variable tend to be associated with larger values of the other variable.

Here are some key points to explain the answer in detail:

- Correlation coefficient: It is a numerical measure that shows the degree of association between two variables. The coefficient is calculated using a formula that takes into account the covariance and standard deviation of the two variables. The coefficient ranges from -1 to +1, where -1 indicates a perfect negative correlation, 0 indicates no correlation, and +1 indicates a perfect positive correlation.

- Positive correlation: When two variables have a positive correlation, it means that they tend to move in the same direction. For example, if we look at the relationship between height and weight, we would expect taller people to weigh more than shorter people. In this case, the correlation coefficient would be positive, and the closer it is to +1, the stronger the correlation.

- Larger values: When we say that larger values of one variable tend to be associated with larger values of the other variable, it means that as one variable increases, the other variable also tends to increase. For example, if we look at the relationship between studying and grades, we would expect students who study more to get higher grades. In this case, the correlation coefficient would be positive, and the closer it is to +1, the stronger the correlation.

- Tendency: The word "tendency" in the statement indicates that the correlation is not a perfect relationship, but rather a general trend. In other words, there may be some variation in the data, and not all cases will follow the same pattern. However, on average, the larger values of one variable will tend to be associated with larger values of the other variable.

In conclusion, the statement is true because a coefficient near 1 indicates a strong positive correlation, which means that the larger values of one variable tend to be associated with larger values of the other variable.