def job_out_series(job_outs, eval_style, method, 
				   value_or_time='value', avg_stdev='avg'):
	""" Takes in some result or resultList objects and 
		a 'method', and desired object, and returns these objects
		in a list
	ARGS:
		results: Result[] or ResultList[], results to consider
		eval_style: str - which method of Experiment we look at
		method: str - which Lipschitz-estimation technique to consider
		value_or_time: 'value' or 'time' - which number to return 
		avg_stdev: 'avg' or 'stdev' - for ResultList[], we can 
				   get average or stdev values 
	RETURNS:
		list of floats
	"""
	# check everything is the same type
	assert value_or_time in ['value', 'time']
	assert avg_stdev in ['avg', 'stdev']
	assert eval_style in ['do_random_evals', 'do_unit_hypercube_eval',
						      'do_data_evals', 'do_large_radius_evals']

	results = [job_out[eval_style] for job_out in job_outs]
	output = []
	for result in results:
		try: #Result object case
			if value_or_time == 'value':
				output.append(result.values(method))
			else:
				output.append(result.compute_times(method))
		except:
			triple = result.average_stdevs(value_or_time)[method]
			if avg_stdev == 'avg':
				output.append(triple[0])
			else:
				output.append(triple[1])
	return output