DOCTORATE WRITERS: Using this Discussion, post questions you have about using SPSS and collaborate with your colleagues to complete Assignment 2, assigned and due this week

DOCTORATE WRITERS: Using this Discussion, post questions you have about using SPSS and collaborate with your colleagues to complete Assignment 2, assigned and due this week

Correlations

Correlational studies or research plays a crucial role in helping researchers gain insight into how particular study variables are related. Through correlational statistics or studies, individuals get to know the strength of a correlation between the variables, and through careful interpretation, a researcher can have an idea if there is a statistically relevant relationship or association (Janse et al.,2021). Therefore, the purpose of this assignment is to explore how to interpret results obtained through a correlational analysis. As such, a correlation SPSS output will be evaluated, and various questions will answered.

The Strongest Correlation In the Matrix

In the provided output, the strongest correlation is between Body Mass Index and weight pounds. It is evident that the Pearson correlation coefficient for the relationship between BMI and Weight-pounds is 0.937. It is important to note that this relationship is significant as a two-tailored significance has been pegged at 0.01 (Makowski et al.,2020).

The Weakest Correlation In the Matrix

            It is also important to explore the weakest correlation in the matrix. From the output, the weakest correlation is the correlation between the Body Mass Index and SF12: Mental Health Component score, standardized. The correlation value is -0.078, which indicates a weak correlation.

The Number of Original Correlations In the Matrix

From the provided output, there are a total of nine correlations. The correlation includes Number of doctor visits, past 12 months and Body Mass Index, Number of doctor visits, past 12 months, and SF12: physical health component score. The next is the Number of doctor visits, past 12 months, and SF12: Mental Health Component Score, standardized; the BMI and SF12: Physical Health Component Score standardized, and Body Mass Index and Weight-pounds. The next correlations are BMI and Weight, SF12: Physical Health Component Score, standardized, and SF12: Mental Health Component Score, standardized. The other includes SF12:Physical Health Component Score, standardized and Body Mass Index, SF12: Mental Health Component Score, standardized, and Number of doctor visits, past 12 months.

What the Entry of 1.00 Indicates on the Diagonal of the Matrix

            The entry of 1.00 on the diagonal matrix indicates that each variable is in perfect correlation with itself (Pandey, 2020). It is easily observable as it is indicated from the top left to the bottom right of the main diagonal.

The Strength and Direction of The Relationship Between BMI and Physical Health

Component Subscale

            The strength of the correlation between body mass index and the physical health component subscale is -0.134. In terms of direction, it is negative, which implies that when the BMI increases, the physical health component subscale decreases. It implies that the two variables are inversely related. In addition, it shows a weak relationship.

The Variable That Is Most Strongly Correlated With BMI, Coefficient, and Sample Size

            From the SPSS output, the variable that is most strongly correlated with Body Mass Index is the Weigh-pounds. The correlational coefficient between the two variables is 0.937. In addition, the sample size for the relationship between Body Mass Index and Weight-pounds is 970. The correlation indicates a very strong positive relationship. The direction is positive, which shows that when the Body Mass Index is high, there is a substantial increase in the weight in pounds. In addition, the strong positive correlation is an indication that a positive and close connection exists between weight in pounds and body mass index.

The Mean and Standard Deviation for BMI and Doctor Visits

From the output, the mean for Body Mass Index is 29.222, with a standard deviation of 7.379. In addition, the mean for the Number of Doctor Visits in the past 12 months is 6.80, with a standard deviation of 12.720.

The Mean and Standard Deviation for Weight and BMI

            From the provided output, the mean for BMI is 29.22, with a standard deviation of 7.38. besides, the mean of weight-pounds is 171.462, with a standard deviation of 7.38.

The Strength and Direction of the Relationship Between