I examine the relation of written language of investors and investment performance of investors.

N=52

Dep. variable -> investment success; binary (1/0) (Acquisition/no Acquisition) (N = 28/22)

Ind. variables -> many language measures; in percent of total language

First step should be to find language variables that might relate to investment success.

I want to perform either a two sample t-test or a Mann-Whitney U-test of a lot of linguistic measures to compare the samples of successful and not successful investments.

Now the question is which test to choose, because...

1.) ... t-test might be problematic, because the two samples mostly aren't normally distributed. My professor told me not to transform the measures when comparing the two samples.

2.) Mann-Whitney might be problematic, because I subsequently want to deepen the analysis and perform correlations and logistic regression. Because of the small sample size I was advised to run a OLS regression to double check my results from the logistic regression.

Let me summarize my problem:

• Is the Mann-Whitney enough when I want to do other analyses later on?

• Wouldn't it make more sense to perform t-tests, because I have to perform an OLS regression at a later stage?

I examine the relation of written language of investors and investment performance of investors.

N=52

Dep. variable -> investment success; binary (1/0) (Acquisition/no Acquisition) (N = 28/22)

Ind. variables -> many language measures; in percent of total language

First step should be to find language variables that might relate to investment success.

I want to perform either a two sample t-test or a Mann-Whitney U-test of a lot of linguistic measures to compare the samples of successful and not successful investments.

Now the question is which test to choose, because...

1. t-test might be problematic, because the two samples mostly aren't normally distributed. My professor told me not to transform the measures when comparing the two samples.

2. Mann-Whitney might be problematic, because I subsequently want to deepen the analysis and perform correlations and logistic regression. Because of the small sample size I was advised to run a OLS regression to double check my results from the logistic regression.

Let me summarize my problem:

• Is the Mann-Whitney enough when I want to do other analyses later on?

• Wouldn't it make more sense to perform t-tests, because I have to perform an OLS regression at a later stage?

i really hope for helpful advice concerning the choice of tests and my research procedure.

I examine the relation of written language of investors and investment performance of investors.

N=52

Dep. variable -> investment success; binary (1/0) (Acquisition/no Acquisition) (N = 28/22)

Ind. variables -> many language measures; in percent of total language

First step should be to find language variables that might relate to investment success.

I want to perform either a two sample t-test or Mann-Whitney-U-test of a lot of linguisitc measures in order to compare the samples of successful and not successful investments.

Now the question is which test to choose, because...

1.) ... t-test might be problematic, because the two samples mostly aren't normally distributed. My professor told me not to transform the measures when comparing the two samples.

2.) Mann-Whitney might be problematic, because I subseqeuntly want to deepen the analysis and perform correlations and logistic regression. Because of the small sample size I was adviced to additionally run a OLS regression to double check my results from the logistic regression.

I know this seems to be pretty complex. So let me try to wrap up my problem.

• Is the Mann-Whitney enough when I want to do other analyses later on?
• Wouldn't it make more sense to perform t-tests, because I have to perform an OLS regression at a later stage.

Any advice is highly appreciated. I really tried to describe the problem as detailed as possible.

Thanks a lot in advance, Tobi

I examine the relation of written language of investors and investment performance of investors.

N=52

Dep. variable -> investment success; binary (1/0) (Acquisition/no Acquisition) (N = 28/22)

Ind. variables -> many language measures; in percent of total language

First step should be to find language variables that might relate to investment success.

I want to perform either a two sample t-test or a Mann-Whitney U-test of a lot of linguistic measures to compare the samples of successful and not successful investments.

Now the question is which test to choose, because...

1.) ... t-test might be problematic, because the two samples mostly aren't normally distributed. My professor told me not to transform the measures when comparing the two samples.

2.) Mann-Whitney might be problematic, because I subsequently want to deepen the analysis and perform correlations and logistic regression. Because of the small sample size I was advised to run a OLS regression to double check my results from the logistic regression.

Let me summarize my problem:

• Is the Mann-Whitney enough when I want to do other analyses later on?

• Wouldn't it make more sense to perform t-tests, because I have to perform an OLS regression at a later stage?