Answer:
 
 
  
 
  
Comparing the p value with a significance level for example  we see that
 we see that  so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can conclude that the true means are not significantly different.
 so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can conclude that the true means are not significantly different.  
Step-by-step explanation:
Data given and notation
 represent the mean for A
 represent the mean for A
 represent the mean for B
 represent the mean for B
 represent the sample standard deviation for A
 represent the sample standard deviation for A
 represent the sample standard deviation for B
 represent the sample standard deviation for B
 sample size for the group A
 sample size for the group A  
 sample size for the group B
 sample size for the group B
 Significance level provided
 Significance level provided  
t would represent the statistic (variable of interest)  
Concepts and formulas to use  
We need to conduct a hypothesis in order to check if the means are equal or not, the system of  hypothesis would be:  
Null hypothesis: 
  
Alternative hypothesis: 
  
We don't have the population standard deviation's but we assume that the population deviation is equal for both populations, so we can apply a t test to compare means, and the statistic is given by:  
 (1)
 (1)  
Where  represent the standard deviation pooled given by:
 represent the standard deviation pooled given by:
 
 
t-test: Is used to compare group means. Is one of the most common tests and is used to determine whether the means of two groups are equal to each other.  
With the info given we can replace in formula (1) like this:  
 
  
P value  
We need to find first the degrees of freedom given by:
 
Since is a two tailed test the p value would be:  
 
  
Comparing the p value with a significance level for example  we see that
 we see that  so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can conclude that the true means are not significantly different.
 so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can conclude that the true means are not significantly different.